Internet-of-Things and Information Fusion: Trust Perspective Survey
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Context-Aware Trustworthy Service Evaluation in Social Internet of Things

paper_content:

In Social Internet of Things (SIoT) environments, a large number of users and Internet of Things (IoT) based devices are connected to each other, so that they can share SIoT-based services. IoT-based devices establish social relations with each other according to the social relations of their owners in Online Social Networks (OSNs). In such an environment, a big challenge is how to provide trustworthy service evaluation. Currently, the prevalent trust management mechanisms consider QoS-based trust and social-relation based trust mechanisms in evaluating the trustworthiness of service providers. However, the existing trust management mechanisms in SIoT environments do not consider the different contexts of trust. Therefore, dishonest SIoT devices, based on their owners’ social relations, can succeed in advertising low-quality services or exploiting maliciously provided services. In this paper, we first propose three contexts of trust in SIoT environments including the status and environment (time and location) of devices, and the types of tasks. Then, we propose a novel Mutual Context-aware Trustworthy Service Evaluation (MCTSE) model. The experiments demonstrate that our proposed contextual trust evaluation model can effectively differentiate honest and dishonest devices and provide a high success rate in selecting the most trustworthy services and providing high resilience against different attacks from dishonest devices.
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paper_title: Towards minimum-delay and energy-efficient flooding in low-duty-cycle wireless sensor networks

paper_content:

Abstract Wireless sensor networks (WSNs) play a very important role in realizing Internet of Things (IoT). In many WSN applications, flooding is a fundamental network service for remote network configuration, diagnosis or disseminating code updates. Despite a plethora of research on flooding problem in the literature, there has been very limited research on flooding tree construction in asynchronous low-duty-cycle WSNs. In this paper, we focus our investigation on minimum-delay and energy-efficient flooding tree construction considering the duty-cycle operation and unreliable wireless links. We show the existence of the latency-energy trade-off in flooding. We formulate the problem as a undetermined-delay-constrained minimum spanning tree (UDC-MST) problem, where the delay constraint is known a posteriori. Due to the NP-completeness of the UDC-MST problem, we design a distributed Minimum-Delay Energy-efficient flooding Tree (MDET) algorithm to construct an energy optimal tree with flooding delay bounding. Through extensive simulations, we demonstrate that MDET achieves a comparable delivery latency with the minimum-delay flooding, and incurs only 10% more transmission cost than the lower bound, which yields a good balance between flooding delay and energy efficiency.
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paper_title: Trust-Based Distributed Kalman Filtering for Target Tracking under Malicious Cyber Attacks

paper_content:

As one of the widely used applications in wireless sensor networks, target tracking has attracted considerable attention. Although many tracking techniques have been developed, it is still a challenging problem if the network is under cyber attacks. Inaccurate or false information is maliciously broadcast by the compromised nodes to their neighbors. They are likely to threaten the security of the system and result in performance deterioration. In this paper, a distributed Kalman filtering technique with trust-based dynamic combination strategy is developed to improve resilience against cyber attacks. Furthermore, it is efficient in terms of communication load, only local instantaneous estimates are exchanged with the neighboring nodes. Numerical results are provided to evaluate the performance of the proposed approach by considering random, false data injection and replay attacks.
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paper_title: Overlay Virtualized Wireless Sensor Networks for Application in Industrial Internet of Things: A Review

paper_content:

In recent times, Wireless Sensor Networks (WSNs) are broadly applied in the Industrial Internet of Things (IIoT) in order to enhance the productivity and efficiency of existing and prospective manufacturing industries. In particular, an area of interest that concerns the use of WSNs in IIoT is the concept of sensor network virtualization and overlay networks. Both network virtualization and overlay networks are considered contemporary because they provide the capacity to create services and applications at the edge of existing virtual networks without changing the underlying infrastructure. This capability makes both network virtualization and overlay network services highly beneficial, particularly for the dynamic needs of IIoT based applications such as in smart industry applications, smart city, and smart home applications. Consequently, the study of both WSN virtualization and overlay networks has become highly patronized in the literature, leading to the growth and maturity of the research area. In line with this growth, this paper provides a review of the development made thus far concerning virtualized sensor networks, with emphasis on the application of overlay networks in IIoT. Principally, the process of virtualization in WSN is discussed along with its importance in IIoT applications. Different challenges in WSN are also presented along with possible solutions given by the use of virtualized WSNs. Further details are also presented concerning the use of overlay networks as the next step to supporting virtualization in shared sensor networks. Our discussion closes with an exposition of the existing challenges in the use of virtualized WSN for IIoT applications. In general, because overlay networks will be contributory to the future development and advancement of smart industrial and smart city applications, this review may be considered by researchers as a reference point for those particularly interested in the study of this growing field.
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paper_title: Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks

paper_content:

Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy.
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paper_title: Multidimensional Trust-Based Anomaly Detection System in Internet of Things

paper_content:

Trust Management (TM) has been playing an important role in dealing with security and privacy issues in the Internet of Things (IoT). Following this trend, we propose a trust-based anomaly detection system which provides a closed loop of trustworthiness computing, decision-making and trust reevaluation. The proposed trust model considers multidimensional trust elements including reputation, Quality of Service (QoS) and social relationship, the result of which is employed to instruct the device to take appropriate security policies against its peers. Moreover, the detected anomaly event will trigger the reevaluation of the peers trustworthiness. To evaluate our system, we consider a shopping mall scenario with a great many of IoT devices, and the simulation results show our system achieves very low false alarm rate under proper trust level threshold.
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paper_title: A multi-level study of information trust models in WSN-assisted IoT

paper_content:

Abstract The Internet of Things (IoT) comprises heterogeneous and interconnected objects. It tries to provide information anytime, anywhere and for anything. The IoT incorporates a variety of technologies, mainly the Wireless Sensor Networks (WSNs). In such networks, sensors are deployed in an open and unprotected environment. Their role is essentially to supervise the environment and report real life phenomena. Only trusted and accurate data should be exchanged between sensors and transmitted to the fusion node which will take charge of the extraction of reliable information. To reach this purpose, we propose that trust should be established at three levels. In this paper, we provide a survey on recent advances in data perception trust (trust in the raw sensed data), communication trust (trust relationship between sensors) and data fusion trust (trust in the fusion process). Moreover, we investigate the existing research to identify their challenges and to suggest future research prospects.
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paper_title: A Practical Evaluation of a High-Security Energy-Efficient Gateway for IoT Fog Computing Applications

paper_content:

Fog computing extends cloud computing to the edge of a network enabling new Internet of Things (IoT) applications and services, which may involve critical data that require privacy and security. In an IoT fog computing system, three elements can be distinguished: IoT nodes that collect data, the cloud, and interconnected IoT gateways that exchange messages with the IoT nodes and with the cloud. This article focuses on securing IoT gateways, which are assumed to be constrained in terms of computational resources, but that are able to offload some processing from the cloud and to reduce the latency in the responses to the IoT nodes. However, it is usually taken for granted that IoT gateways have direct access to the electrical grid, which is not always the case: in mission-critical applications like natural disaster relief or environmental monitoring, it is common to deploy IoT nodes and gateways in large areas where electricity comes from solar or wind energy that charge the batteries that power every device. In this article, how to secure IoT gateway communications while minimizing power consumption is analyzed. The throughput and power consumption of Rivest–Shamir–Adleman (RSA) and Elliptic Curve Cryptography (ECC) are considered, since they are really popular, but have not been thoroughly analyzed when applied to IoT scenarios. Moreover, the most widespread Transport Layer Security (TLS) cipher suites use RSA as the main public key-exchange algorithm, but the key sizes needed are not practical for most IoT devices and cannot be scaled to high security levels. In contrast, ECC represents a much lighter and scalable alternative. Thus, RSA and ECC are compared for equivalent security levels, and power consumption and data throughput are measured using a testbed of IoT gateways. The measurements obtained indicate that, in the specific fog computing scenario proposed, ECC is clearly a much better alternative than RSA, obtaining energy consumption reductions of up to 50% and a data throughput that doubles RSA in most scenarios. These conclusions are then corroborated by a frame temporal analysis of Ethernet packets. In addition, current data compression algorithms are evaluated, concluding that, when dealing with the small payloads related to IoT applications, they do not pay off in terms of real data throughput and power consumption.
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paper_title: An Efficient Architecture for Trust Management in IoE Based Systems of Systems

paper_content:

Internet of Every things (IoE) is a network that integrates a variety of heterogeneous nodes, such as connected portable devices, connected cars, smart home appliances, humans, etc. to Internet. The constituents of IoE are heterogeneous, distributed by nature and also autonomous in most of cases, which meet the criteria of what we call Systems of Systems (SoS). These smart objects communicate and collaborate between each other in dynamic environments which are subject to several security attacks. In this paper, we propose a hierarchical based blockchain trust management architecture with mobility support in highly distributed IoE based Systems of Systems. This architecture deals efficiently with scalability issues. It allows smart objects to disseminate the trustworthiness of the service providers they interact with them to the blockchain. This later makes the access to this information possible from anywhere and ensures a global view of trustworthiness information. Thanks to the blockchain technology, our architecture outperforms the existing trust management solutions especially in terms of scalability and mobility support.
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paper_title: Clarifying Trust in Social Internet of Things

paper_content:

A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy relationships among the objects greatly improves the effectiveness of node interaction in the social IoT and helps nodes overcome perceptions of uncertainty and risk. However, there are limitations in the existing trust models. In this paper, a comprehensive model of trust is proposed that is tailored to the social IoT. The model includes ingredients such as trustor, trustee, goal, trustworthiness evaluation, decision, action, result, and context. Building on this trust model, we clarify the concepts of trust in the social IoT in five aspects such as: 1) mutuality of trustor and trustee; 2) inferential transfer of trust; 3) transitivity of trust; 4) trustworthiness update; and 5) trustworthiness affected by dynamic environment. With network connectivities that are from real-world social networks, a series of simulations are conducted to evaluate the performance of the social IoT operated with the proposed trust model. An experimental IoT network is used to further validate the proposed trust model.
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paper_title: Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes

paper_content:

The Internet of Things (IoT) is an emerging paradigm focusing on the connection of devices, objects, or “things” to each other, to the Internet, and to users. IoT technology is anticipated to become an essential requirement in the development of smart homes, as it offers convenience and efficiency to home residents so that they can achieve better quality of life. Application of the IoT model to smart homes, by connecting objects to the Internet, poses new security and privacy challenges in terms of the confidentiality, authenticity, and integrity of the data sensed, collected, and exchanged by the IoT objects. These challenges make smart homes extremely vulnerable to different types of security attacks, resulting in IoT-based smart homes being insecure. Therefore, it is necessary to identify the possible security risks to develop a complete picture of the security status of smart homes. This article applies the operationally critical threat, asset, and vulnerability evaluation (OCTAVE) methodology, known as OCTAVE Allegro, to assess the security risks of smart homes. The OCTAVE Allegro method focuses on information assets and considers different information containers such as databases, physical papers, and humans. The key goals of this study are to highlight the various security vulnerabilities of IoT-based smart homes, to present the risks on home inhabitants, and to propose approaches to mitigating the identified risks. The research findings can be used as a foundation for improving the security requirements of IoT-based smart homes.
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paper_title: Privacy-Preserving Authentication Using a Double Pseudonym for Internet of Vehicles

paper_content:

The Internet of Vehicles (IoV) plays an important role in smart transportation to reduce the drivers’s risk of having an accident and help them manage small emergencies. Therefore, security and privacy issues of the message in the tamper proof device (TPD) broadcasted to other vehicles and roadside units (RSUs) have become an important research subject in the field of smart transportation. Many authentication schemes are proposed to tackle the challenges above and most of them are heavy in computation and communication. In this paper, we propose a novel authentication scheme that utilizes the double pseudonym method to hide the real identity of vehicles and adopts the dynamic update technology to periodically update the information (such as member secret, authentication key, internal pseudo-identity) stored in the tamper-proof device to prevent the side-channel attack. Because of not using bilinear pairing, our scheme yields a better performance in terms of computation overhead and communication overhead, and is more suitable to be applied in the Internet of Vehicles.
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paper_title: Mitigating the effect of free riders in distributed systems: a trust-based approach

paper_content:

Distributed systems such as the grid, the cloud, and wireless sensor networks WSNs often involve cooperation and consequently require secure resource sharing across organisational boundaries. This adds an extra overhead that might negate the benefits of using these systems. WSNs and P2P services have similar underlying technologies and similar applications. One major problem hindering the success of these ubiquitous services is free riding. Many free riding algorithms proposed in the literature assume that all sensors are honest and collusion-free. These assumptions do not hold in environments such as WSNs and P2P, where autonomy and public subscription are key attributes. In this paper, we propose a free riding mitigation algorithm to countermeasure two types of attacks, namely dishonesty and collusion. We also conduct extensive experiments to evaluate our proposed solution.
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paper_title: A Reference Model for Monitoring IoT WSN-Based Applications

paper_content:

The Internet of Things (IoT) is, at this moment, one of the most promising technologies that has arisen for decades. Wireless Sensor Networks (WSNs) are one of the main pillars for many IoT applications, insofar as they require to obtain context-awareness information. The bibliography shows many difficulties in their real implementation that have prevented its massive deployment. Additionally, in IoT environments where data producers and data consumers are not directly related, compatibility and certification issues become fundamental. Both problems would profit from accurate knowledge of the internal behavior of WSNs that must be obtained by the utilization of appropriate tools. There are many ad-hoc proposals with no common structure or methodology, and intended to monitor a particular WSN. To overcome this problem, this paper proposes a structured three-layer reference model for WSN Monitoring Platforms (WSN-MP), which offers a standard environment for the design of new monitoring platforms to debug, verify and certify a WSN's behavior and performance, and applicable to every WSN. This model also allows the comparative analysis of the current proposals for monitoring the operation of WSNs. Following this methodology, it is possible to achieve a standardization of WSN-MP, promoting new research areas in order to solve the problems of each layer.
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paper_title: An Energy-Efficient Reliable Trust-Based Data Aggregation Protocol for Wireless Sensor Networks

paper_content:

Security data aggregation plays an important role in reducing the amount of data transmission and prolonging the life of wireless sensor networks (WSN). When the security of the aggregation nodes is threatened, the networks can generate many aggregated data errors, leading to trouble in a security measure. In this paper, we propose an energy-efficient reliable trust-based data aggregation protocol for WSN called the ERTDA protocol. Based on the observations of the nodal behavior, the ERTDA protocol calculates, monitors and evaluates the trust values of the nodes; it also detects and excludes the compromised nodes in a timely manner. The simulation results illustrate that the ERTDA protocol can effectively improve the accuracy of the aggregation, reduce the nodal mortality rate, reduce the nodal energy consumption, improve the reliability of the data transmission and extend the life of the networks.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Trust-Based Distributed Kalman Filtering for Target Tracking under Malicious Cyber Attacks

paper_content:

As one of the widely used applications in wireless sensor networks, target tracking has attracted considerable attention. Although many tracking techniques have been developed, it is still a challenging problem if the network is under cyber attacks. Inaccurate or false information is maliciously broadcast by the compromised nodes to their neighbors. They are likely to threaten the security of the system and result in performance deterioration. In this paper, a distributed Kalman filtering technique with trust-based dynamic combination strategy is developed to improve resilience against cyber attacks. Furthermore, it is efficient in terms of communication load, only local instantaneous estimates are exchanged with the neighboring nodes. Numerical results are provided to evaluate the performance of the proposed approach by considering random, false data injection and replay attacks.
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paper_title: Trust modeling and its applications for peer-to-peer based systems

paper_content:

Organizing large-scale network computing systems in a peer-to-peer (P2P) fashion is a manifestation of one of the fundamental design principles on the Internet. Current research is focusing on improving P2P systems and one of the future directions is to combine P2P and Grid technologies. One of the key issues identified in the evolution of P2P technologies is the trust issue. ::: This thesis presents a trust model for P2P structured large-scale network computing systems. The most widely used trust modeling approach is to use a network of recommenders to obtain references and use these to predict the trust between two entities. This approach is known to suffer from drawbacks such as trustworthiness of the recommenders and scalability. ::: To address this problem, a solution is proposed where a recommender is independently evaluated using accuracy and honesty measures. This thesis explains using simulation results how the separation of accuracy and honesty helps in addressing the above issues. To demonstrate the utility of the trust model, a trust aware resource allocation model is developed such that it can be used to make trust cognizant resource allocations. To the best of our knowledge, this is the first study to integrate trust into resource management systems. The simulation results indicate that significant preferences gain can be obtained through this integration.
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paper_title: Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

paper_content:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
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paper_title: SORT: A Self-ORganizing Trust Model for Peer-to-Peer Systems

paper_content:

Open nature of peer-to-peer systems exposes them to malicious activity. Building trust relationships among peers can mitigate attacks of malicious peers. This paper presents distributed algorithms that enable a peer to reason about trustworthiness of other peers based on past interactions and recommendations. Peers create their own trust network in their proximity by using local information available and do not try to learn global trust information. Two contexts of trust, service, and recommendation contexts, are defined to measure trustworthiness in providing services and giving recommendations. Interactions and recommendations are evaluated based on importance, recentness, and peer satisfaction parameters. Additionally, recommender's trustworthiness and confidence about a recommendation are considered while evaluating recommendations. Simulation experiments on a file sharing application show that the proposed model can mitigate attacks on 16 different malicious behavior models. In the experiments, good peers were able to form trust relationships in their proximity and isolate malicious peers.
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paper_title: Toward a Trust Evaluation Mechanism in the Social Internet of Things

paper_content:

In the blooming era of the Internet of Things (IoT), trust has been accepted as a vital factor for provisioning secure, reliable, seamless communications and services. However, a large number of challenges still remain unsolved due to the ambiguity of the concept of trust as well as the variety of divergent trust models in different contexts. In this research, we augment the trust concept, the trust definition and provide a general conceptual model in the context of the Social IoT (SIoT) environment by breaking down all attributes influencing trust. Then, we propose a trust evaluation model called REK, comprised of the triad of trust indicators (TIs) Reputation, Experience and Knowledge. The REK model covers multi-dimensional aspects of trust by incorporating heterogeneous information from direct observation (as Knowledge TI), personal experiences (as Experience TI) to global opinions (as Reputation TI). The associated evaluation models for the three TIs are also proposed and provisioned. We then come up with an aggregation mechanism for deriving trust values as the final outcome of the REK evaluation model. We believe this article offers better understandings on trust as well as provides several prospective approaches for the trust evaluation in the SIoT environment.
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paper_title: Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

paper_content:

Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.
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paper_title: TIDY: A trust-based approach to information fusion through diversity

paper_content:

Trust and reputation are significant components in open dynamic systems for making informed and reliable decisions. State-of-the-art information fusion models that exploit these mechanisms generally rely on reports from as many sources as possible. Situations exist, however, where seeking evidence from all possible sources is unrealistic. Querying information sources is costly especially in resource-constrained environments, in terms of time and bandwidth. In addition, reports from multiple sources expose one to the risk of double-counting evidence, introducing an extra challenge of distinguishing fact from rumour. This paper describes TIDY (Trust-based Information fusion through DiversitY), a trust-based approach to information fusion that exploits diversity among information sources in order to select a small number of candidates to query for evidence, and to minimise the effect of correlated evidence and bias. We demonstrate that reliable decisions can be reached using evidence from small groups of individuals. We show empirically that our approach is robust in contexts of variable trust in information sources, and to a degree of deception.
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paper_title: From Personal Experience to Global Reputation for Trust Evaluation in the Social Internet of Things

paper_content:

Trust has been exploring in the era of Internet of Things (IoT) as an extension of the traditional triad of security, privacy and reliability for offering secure, reliable and seamless communications and services. It plays a crucial role in supporting IoT entities to reduce possible risks before making decisions. However, despite a large amount of trust-related research in IoT, a prevailing trust evaluation model has been still debatable and under development. In this article, we clarify the concept of trust in the Social Internet of Things (SIoT) ecosystems and propose a comprehensive trust model called REK that incorporates third-party opinions, experience and direct observation as the three Trust Indicators. As the convergence of the IoT and social network, the SIoT enables any types of entities (physical devices, smart agents and services) to establish their own social networks based on their owners' relationships. We leverage this characteristic for inaugurating Experience and Reputation, which are originally two concepts from social networks, as the two paramount indicators for trust. The Experience and Reputation are characterized and modeled using mathematical analysis along with simulation experiments and analytical results. We believe our contributions offer better understandings of trust models and evaluation mechanisms in the SIoT environment, particularly the two Experience and Reputation models. This paper also opens important trust-related research directions in near future.
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paper_title: A Survey on Trust Management for Mobile Ad Hoc Networks

paper_content:

Managing trust in a distributed Mobile Ad Hoc Network (MANET) is challenging when collaboration or cooperation is critical to achieving mission and system goals such as reliability, availability, scalability, and reconfigurability. In defining and managing trust in a military MANET, we must consider the interactions between the composite cognitive, social, information and communication networks, and take into account the severe resource constraints (e.g., computing power, energy, bandwidth, time), and dynamics (e.g., topology changes, node mobility, node failure, propagation channel conditions). We seek to combine the notions of "social trust" derived from social networks with "quality-of-service (QoS) trust" derived from information and communication networks to obtain a composite trust metric. We discuss the concepts and properties of trust and derive some unique characteristics of trust in MANETs, drawing upon social notions of trust. We provide a survey of trust management schemes developed for MANETs and discuss generally accepted classifications, potential attacks, performance metrics, and trust metrics in MANETs. Finally, we discuss future research areas on trust management in MANETs based on the concept of social and cognitive networks.
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paper_title: Trust architecture and reputation evaluation for internet of things

paper_content:

Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and reputation evaluation. However, existing trust architectures and reputation evaluation solutions cannot be directly applied to the IoT, due to the large number of physical entities, the limited computation ability of physical entities, and the highly dynamic nature of the network. In comparison, it generally requires a general and flexible architecture to manage trust in such a dynamic environment as IoT. In this paper, we present IoTrust, a trust architecture that integrates Soft Defined Network (SDN) in IoT, and a cross-layer authorization protocol based on IoTrust. IoTrust and the protocol together provide a new insight for research on trust management in the IoT. For trust establishment, we further propose a Behavior-based Reputation Evaluation Scheme for the Node (BES) and an Organization Reputation Evaluation Scheme (ORES). Both our theoretical analysis and simulation results validate the efficiency of BES and ORES.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
---
paper_title: Trust-Based Distributed Kalman Filtering for Target Tracking under Malicious Cyber Attacks

paper_content:

As one of the widely used applications in wireless sensor networks, target tracking has attracted considerable attention. Although many tracking techniques have been developed, it is still a challenging problem if the network is under cyber attacks. Inaccurate or false information is maliciously broadcast by the compromised nodes to their neighbors. They are likely to threaten the security of the system and result in performance deterioration. In this paper, a distributed Kalman filtering technique with trust-based dynamic combination strategy is developed to improve resilience against cyber attacks. Furthermore, it is efficient in terms of communication load, only local instantaneous estimates are exchanged with the neighboring nodes. Numerical results are provided to evaluate the performance of the proposed approach by considering random, false data injection and replay attacks.
---
paper_title: Trust modeling and its applications for peer-to-peer based systems

paper_content:

Organizing large-scale network computing systems in a peer-to-peer (P2P) fashion is a manifestation of one of the fundamental design principles on the Internet. Current research is focusing on improving P2P systems and one of the future directions is to combine P2P and Grid technologies. One of the key issues identified in the evolution of P2P technologies is the trust issue. ::: This thesis presents a trust model for P2P structured large-scale network computing systems. The most widely used trust modeling approach is to use a network of recommenders to obtain references and use these to predict the trust between two entities. This approach is known to suffer from drawbacks such as trustworthiness of the recommenders and scalability. ::: To address this problem, a solution is proposed where a recommender is independently evaluated using accuracy and honesty measures. This thesis explains using simulation results how the separation of accuracy and honesty helps in addressing the above issues. To demonstrate the utility of the trust model, a trust aware resource allocation model is developed such that it can be used to make trust cognizant resource allocations. To the best of our knowledge, this is the first study to integrate trust into resource management systems. The simulation results indicate that significant preferences gain can be obtained through this integration.
---
paper_title: Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

paper_content:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
---
paper_title: Trust architecture and reputation evaluation for internet of things

paper_content:

Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and reputation evaluation. However, existing trust architectures and reputation evaluation solutions cannot be directly applied to the IoT, due to the large number of physical entities, the limited computation ability of physical entities, and the highly dynamic nature of the network. In comparison, it generally requires a general and flexible architecture to manage trust in such a dynamic environment as IoT. In this paper, we present IoTrust, a trust architecture that integrates Soft Defined Network (SDN) in IoT, and a cross-layer authorization protocol based on IoTrust. IoTrust and the protocol together provide a new insight for research on trust management in the IoT. For trust establishment, we further propose a Behavior-based Reputation Evaluation Scheme for the Node (BES) and an Organization Reputation Evaluation Scheme (ORES). Both our theoretical analysis and simulation results validate the efficiency of BES and ORES.
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paper_title: Trust modeling and its applications for peer-to-peer based systems

paper_content:

Organizing large-scale network computing systems in a peer-to-peer (P2P) fashion is a manifestation of one of the fundamental design principles on the Internet. Current research is focusing on improving P2P systems and one of the future directions is to combine P2P and Grid technologies. One of the key issues identified in the evolution of P2P technologies is the trust issue. ::: This thesis presents a trust model for P2P structured large-scale network computing systems. The most widely used trust modeling approach is to use a network of recommenders to obtain references and use these to predict the trust between two entities. This approach is known to suffer from drawbacks such as trustworthiness of the recommenders and scalability. ::: To address this problem, a solution is proposed where a recommender is independently evaluated using accuracy and honesty measures. This thesis explains using simulation results how the separation of accuracy and honesty helps in addressing the above issues. To demonstrate the utility of the trust model, a trust aware resource allocation model is developed such that it can be used to make trust cognizant resource allocations. To the best of our knowledge, this is the first study to integrate trust into resource management systems. The simulation results indicate that significant preferences gain can be obtained through this integration.
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paper_title: Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

paper_content:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
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paper_title: Trust modeling and its applications for peer-to-peer based systems

paper_content:

Organizing large-scale network computing systems in a peer-to-peer (P2P) fashion is a manifestation of one of the fundamental design principles on the Internet. Current research is focusing on improving P2P systems and one of the future directions is to combine P2P and Grid technologies. One of the key issues identified in the evolution of P2P technologies is the trust issue. ::: This thesis presents a trust model for P2P structured large-scale network computing systems. The most widely used trust modeling approach is to use a network of recommenders to obtain references and use these to predict the trust between two entities. This approach is known to suffer from drawbacks such as trustworthiness of the recommenders and scalability. ::: To address this problem, a solution is proposed where a recommender is independently evaluated using accuracy and honesty measures. This thesis explains using simulation results how the separation of accuracy and honesty helps in addressing the above issues. To demonstrate the utility of the trust model, a trust aware resource allocation model is developed such that it can be used to make trust cognizant resource allocations. To the best of our knowledge, this is the first study to integrate trust into resource management systems. The simulation results indicate that significant preferences gain can be obtained through this integration.
---
paper_title: Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

paper_content:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
---
paper_title: Trust modeling and its applications for peer-to-peer based systems

paper_content:

Organizing large-scale network computing systems in a peer-to-peer (P2P) fashion is a manifestation of one of the fundamental design principles on the Internet. Current research is focusing on improving P2P systems and one of the future directions is to combine P2P and Grid technologies. One of the key issues identified in the evolution of P2P technologies is the trust issue. ::: This thesis presents a trust model for P2P structured large-scale network computing systems. The most widely used trust modeling approach is to use a network of recommenders to obtain references and use these to predict the trust between two entities. This approach is known to suffer from drawbacks such as trustworthiness of the recommenders and scalability. ::: To address this problem, a solution is proposed where a recommender is independently evaluated using accuracy and honesty measures. This thesis explains using simulation results how the separation of accuracy and honesty helps in addressing the above issues. To demonstrate the utility of the trust model, a trust aware resource allocation model is developed such that it can be used to make trust cognizant resource allocations. To the best of our knowledge, this is the first study to integrate trust into resource management systems. The simulation results indicate that significant preferences gain can be obtained through this integration.
---
paper_title: Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

paper_content:

The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
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paper_title: Double Cluster Heads Model for Secure and Accurate Data Fusion in Wireless Sensor Networks

paper_content:

Secure and accurate data fusion is an important issue in wireless sensor networks (WSNs) and has been extensively researched in the literature. In this paper, by combining clustering techniques, reputation and trust systems, and data fusion algorithms, we propose a novel cluster-based data fusion model called Double Cluster Heads Model (DCHM) for secure and accurate data fusion in WSNs. Different from traditional clustering models in WSNs, two cluster heads are selected after clustering for each cluster based on the reputation and trust system and they perform data fusion independently of each other. Then, the results are sent to the base station where the dissimilarity coefficient is computed. If the dissimilarity coefficient of the two data fusion results exceeds the threshold preset by the users, the cluster heads will be added to blacklist, and the cluster heads must be reelected by the sensor nodes in a cluster. Meanwhile, feedback is sent from the base station to the reputation and trust system, which can help us to identify and delete the compromised sensor nodes in time. Through a series of extensive simulations, we found that the DCHM performed very well in data fusion security and accuracy.
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paper_title: A multi-level study of information trust models in WSN-assisted IoT

paper_content:

Abstract The Internet of Things (IoT) comprises heterogeneous and interconnected objects. It tries to provide information anytime, anywhere and for anything. The IoT incorporates a variety of technologies, mainly the Wireless Sensor Networks (WSNs). In such networks, sensors are deployed in an open and unprotected environment. Their role is essentially to supervise the environment and report real life phenomena. Only trusted and accurate data should be exchanged between sensors and transmitted to the fusion node which will take charge of the extraction of reliable information. To reach this purpose, we propose that trust should be established at three levels. In this paper, we provide a survey on recent advances in data perception trust (trust in the raw sensed data), communication trust (trust relationship between sensors) and data fusion trust (trust in the fusion process). Moreover, we investigate the existing research to identify their challenges and to suggest future research prospects.
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paper_title: An Energy-Efficient Reliable Trust-Based Data Aggregation Protocol for Wireless Sensor Networks

paper_content:

Security data aggregation plays an important role in reducing the amount of data transmission and prolonging the life of wireless sensor networks (WSN). When the security of the aggregation nodes is threatened, the networks can generate many aggregated data errors, leading to trouble in a security measure. In this paper, we propose an energy-efficient reliable trust-based data aggregation protocol for WSN called the ERTDA protocol. Based on the observations of the nodal behavior, the ERTDA protocol calculates, monitors and evaluates the trust values of the nodes; it also detects and excludes the compromised nodes in a timely manner. The simulation results illustrate that the ERTDA protocol can effectively improve the accuracy of the aggregation, reduce the nodal mortality rate, reduce the nodal energy consumption, improve the reliability of the data transmission and extend the life of the networks.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Securing the Internet of Things

paper_content:

This paper presents security of Internet of things. In the Internet of Things vision, every physical object has a virtual component that can produce and consume services Such extreme interconnection will bring unprecedented convenience and economy, but it will also require novel approaches to ensure its safe and ethical use. The Internet and its users are already under continual attack, and a growing economy-replete with business models that undermine the Internet's ethical use-is fully focused on exploiting the current version's foundational weaknesses.
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paper_title: On security challenges and open issues in Internet of Things

paper_content:

Abstract When Internet of Things (IoT) applications become a part of people’s daily life, security issues in IoT have caught significant attention in both academia and industry. Compared to traditional computing systems, IoT systems have more inherent vulnerabilities, and meanwhile, could have higher security requirements. However, the current design of IoT does not effectively address the higher security requirements posed by those vulnerabilities. Many recent attacks on IoT systems have shown that novel security solutions are needed to protect this emerging system. This paper aims to analyze security challenges resulted from the special characteristics of the IoT systems and the new features of the IoT applications. This could help pave the road to better security solution design. In addition, three architectural security designs are proposed and analyzed. Examples of how to implement these designs are discussed. Finally, for each layer in IoT architecture, open issues are also identified.
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paper_title: Data centric trust evaluation and prediction framework for IOT

paper_content:

Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas.
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paper_title: Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm

paper_content:

Abstract The high penetration rate of new technologies in all the activities of everyday life is fostering the belief that for any new societal challenge there is always an ICT solution able to successfully deal with it. Recently, the solution that is proposed almost anytime is the “Internet of Things” (IoT). This apparent panacea of the ICT world takes different aspects on and, actually, is identified with different (often very different) technological solutions. As a result, many think that IoT is just RFIDs, others think that it is sensor networks, and yet others that it is machine-to-machine communications. In the meanwhile, industrial players are taking advantage of the popularity of IoT to use it as a very trendy brand for technology solutions oriented to the consumer market. The scientific literature sometimes does not help much in clarifying, as it is rich in definitions of IoT often discordant between them. Objective of this paper is to present the evolutionary stages, i.e., generations, that have characterized the development of IoT, along with the motivations of their triggering. Besides, it analyzes the role that IoT can play in addressing the main societal challenges and the set of features expected from the relevant solutions. The final objective is to give a modern definition of the phenomenon, which de facto shows a strong pervasive nature, and, if not well understood in its theories, technologies, methodologies, and real potentials, then runs the risk of being regarded with suspicion and, thus, rejected by users.
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paper_title: Mitigating the effect of free riders in distributed systems: a trust-based approach

paper_content:

Distributed systems such as the grid, the cloud, and wireless sensor networks WSNs often involve cooperation and consequently require secure resource sharing across organisational boundaries. This adds an extra overhead that might negate the benefits of using these systems. WSNs and P2P services have similar underlying technologies and similar applications. One major problem hindering the success of these ubiquitous services is free riding. Many free riding algorithms proposed in the literature assume that all sensors are honest and collusion-free. These assumptions do not hold in environments such as WSNs and P2P, where autonomy and public subscription are key attributes. In this paper, we propose a free riding mitigation algorithm to countermeasure two types of attacks, namely dishonesty and collusion. We also conduct extensive experiments to evaluate our proposed solution.
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paper_title: A Survey on Trust Management for Internet of Things

paper_content:

Internet of Things (IoT) is going to create a world where physical objects are seamlessly integrated into information networks in order to provide advanced and intelligent services for human-beings. Trust management plays an important role in IoT for reliable data fusion and mining, qualified services with context-awareness, and enhanced user privacy and information security. It helps people overcome perceptions of uncertainty and risk and engages in user acceptance and consumption on IoT services and applications. However, current literature still lacks a comprehensive study on trust management in IoT. In this paper, we investigate the properties of trust, propose objectives of IoT trust management, and provide a survey on the current literature advances towards trustworthy IoT. Furthermore, we discuss unsolved issues, specify research challenges and indicate future research trends by proposing a research model for holistic trust management in IoT.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Trust-Based Service Management for Social Internet of Things Systems

paper_content:

A social internet of things (IoT) system can be viewed as a mix of traditional peer-to-peer networks and social networks, where “things” autonomously establish social relationships according to the owners’ social networks, and seek trusted “things” that can provide services needed when they come into contact with each other opportunistically. We propose and analyze the design notion of adaptive trust management for social IoT systems in which social relationships evolve dynamically among the owners of IoT devices. We reveal the design tradeoff between trust convergence versus trust fluctuation in our adaptive trust management protocol design. With our adaptive trust management protocol, a social IoT application can adaptively choose the best trust parameter settings in response to changing IoT social conditions such that not only trust assessment is accurate but also the application performance is maximized. We propose a table-lookup method to apply the analysis results dynamically and demonstrate the feasibility of our proposed adaptive trust management scheme with two real-world social IoT service composition applications.
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paper_title: A multi-level study of information trust models in WSN-assisted IoT

paper_content:

Abstract The Internet of Things (IoT) comprises heterogeneous and interconnected objects. It tries to provide information anytime, anywhere and for anything. The IoT incorporates a variety of technologies, mainly the Wireless Sensor Networks (WSNs). In such networks, sensors are deployed in an open and unprotected environment. Their role is essentially to supervise the environment and report real life phenomena. Only trusted and accurate data should be exchanged between sensors and transmitted to the fusion node which will take charge of the extraction of reliable information. To reach this purpose, we propose that trust should be established at three levels. In this paper, we provide a survey on recent advances in data perception trust (trust in the raw sensed data), communication trust (trust relationship between sensors) and data fusion trust (trust in the fusion process). Moreover, we investigate the existing research to identify their challenges and to suggest future research prospects.
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paper_title: A Reliable and Lightweight Trust Computing Mechanism for IoT Edge Devices Based on Multi-Source Feedback Information Fusion

paper_content:

The integration of Internet of Things (IoT) and edge computing is currently a new research hotspot. However, the lack of trust between IoT edge devices has hindered the universal acceptance of IoT edge computing as outsourced computing services. In order to increase the adoption of IoT edge computing applications, first, IoT edge computing architecture should establish efficient trust calculation mechanism to alleviate the concerns of numerous users. In this paper, a reliable and lightweight trust mechanism is originally proposed for IoT edge devices based on multi-source feedback information fusion. First, due to the multi-source feedback mechanism is used for global trust calculation, our trust calculation mechanism is more reliable against bad-mouthing attacks caused by malicious feedback providers. Then, we adopt lightweight trust evaluating mechanism for cooperations of IoT edge devices, which is suitable for large-scale IoT edge computing because it facilitates low-overhead trust computing algorithms. At the same time, we adopt a feedback information fusion algorithm based on objective information entropy theory, which can overcome the limitations of traditional trust schemes, whereby the trust factors are weighted manually or subjectively. And the experimental results show that the proposed trust calculation scheme significantly outperforms existing approaches in both computational efficiency and reliability.
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paper_title: Trust architecture and reputation evaluation for internet of things

paper_content:

Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and reputation evaluation. However, existing trust architectures and reputation evaluation solutions cannot be directly applied to the IoT, due to the large number of physical entities, the limited computation ability of physical entities, and the highly dynamic nature of the network. In comparison, it generally requires a general and flexible architecture to manage trust in such a dynamic environment as IoT. In this paper, we present IoTrust, a trust architecture that integrates Soft Defined Network (SDN) in IoT, and a cross-layer authorization protocol based on IoTrust. IoTrust and the protocol together provide a new insight for research on trust management in the IoT. For trust establishment, we further propose a Behavior-based Reputation Evaluation Scheme for the Node (BES) and an Organization Reputation Evaluation Scheme (ORES). Both our theoretical analysis and simulation results validate the efficiency of BES and ORES.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions

paper_content:

Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fueled by the recent adaptation of a variety of enabling wireless technologies such as RFID tags and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a Cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A Cloud implementation using Aneka, which is based on interaction of private and public Clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.
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paper_title: A Decentralized Trustworthy Context and QoS-Aware Service Discovery Framework for the Internet of Things

paper_content:

The Internet of Things envisions a multitude of heterogeneous objects and interactions with physical environments. It has provided a promising opportunity to build powerful services and applications by leveraging the growing ubiquity of smart objects connected to the Internet. In this environment, it is challenging to locate desirable services due to the considerable diversity, large scale, dynamic behavior, and geographical distribution of the services provided by physical objects. In this paper, we propose a decentralized semantics-based service discovery framework, which can effectively locate trustworthy services based on requester’s quality of service demands and changing context requirements. The proposed service discovery system is built upon fully distributed peer-to-peer architectures and includes two discovery approaches which are scalable, robust, and trust assured. Moreover, an efficient trust propagation mechanism is proposed, which seamlessly integrates with the proposed service discovery system without adding additional infrastructure overhead. Comprehensive simulation studies have demonstrated the effectiveness of the proposed framework.
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paper_title: Modelling trust dynamics in the Internet of Things

paper_content:

The Internet of Things (IoT) is a paradigm based on the interconnection of everyday objects. It is expected that the things involved in the IoT paradigm will have to interact with each other, often in uncertain conditions. It is therefore of paramount importance for the success of IoT that there are mechanisms in place that help overcome the lack of certainty. Trust can help achieve this goal. In this paper, we introduce a framework that assists developers in including trust in IoT scenarios. This framework takes into account trust, privacy and identity requirements as well as other functional requirements derived from IoT scenarios to provide the different services that allow the inclusion of trust in the IoT.
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paper_title: An Efficient Architecture for Trust Management in IoE Based Systems of Systems

paper_content:

Internet of Every things (IoE) is a network that integrates a variety of heterogeneous nodes, such as connected portable devices, connected cars, smart home appliances, humans, etc. to Internet. The constituents of IoE are heterogeneous, distributed by nature and also autonomous in most of cases, which meet the criteria of what we call Systems of Systems (SoS). These smart objects communicate and collaborate between each other in dynamic environments which are subject to several security attacks. In this paper, we propose a hierarchical based blockchain trust management architecture with mobility support in highly distributed IoE based Systems of Systems. This architecture deals efficiently with scalability issues. It allows smart objects to disseminate the trustworthiness of the service providers they interact with them to the blockchain. This later makes the access to this information possible from anywhere and ensures a global view of trustworthiness information. Thanks to the blockchain technology, our architecture outperforms the existing trust management solutions especially in terms of scalability and mobility support.
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paper_title: Clarifying Trust in Social Internet of Things

paper_content:

A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy relationships among the objects greatly improves the effectiveness of node interaction in the social IoT and helps nodes overcome perceptions of uncertainty and risk. However, there are limitations in the existing trust models. In this paper, a comprehensive model of trust is proposed that is tailored to the social IoT. The model includes ingredients such as trustor, trustee, goal, trustworthiness evaluation, decision, action, result, and context. Building on this trust model, we clarify the concepts of trust in the social IoT in five aspects such as: 1) mutuality of trustor and trustee; 2) inferential transfer of trust; 3) transitivity of trust; 4) trustworthiness update; and 5) trustworthiness affected by dynamic environment. With network connectivities that are from real-world social networks, a series of simulations are conducted to evaluate the performance of the social IoT operated with the proposed trust model. An experimental IoT network is used to further validate the proposed trust model.
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paper_title: A Mobile Cloud Hierarchical Trust Management Protocol for IoT Systems

paper_content:

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust management protocol called IoT-HiTrust for large-scale IoT systems. Our mobile cloud hierarchical trust management protocol allows an IoT device to report its service experiences and query the trustworthiness of another IoT device for service composition and selection following a simple localized report-and-query paradigm. We verify IoT-HiTrust's conver-gence, accuracy, and resiliency properties against self-promotion, discriminatory, bad-mouthing, ballot-stuffing, and opportunistic service attacks despite intermittent network disconnection to the cloud.
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paper_title: TRAVOS: Trust and Reputation in the Context of Inaccurate Information Sources

paper_content:

In many dynamic open systems, agents have to interact with one another to achieve their goals. Here, agents may be self-interested, and when trusted to perform an action for another, may betray that trust by not performing the action as required. In addition, due to the size of such systems, agents will often interact with other agents with which they have little or no past experience. There is therefore a need to develop a model of trust and reputation that will ensure good interactions among software agents in large scale open systems. Against this background, we have developed TRAVOS (Trust and Reputation model for Agent-based Virtual OrganisationS) which models an agent's trust in an interaction partner. Specifically, trust is calculated using probability theory taking account of past interactions between agents, and when there is a lack of personal experience between agents, the model draws upon reputation information gathered from third parties. In this latter case, we pay particular attention to handling the possibility that reputation information may be inaccurate.
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paper_title: Are My Arguments Trustworthy? Abstract Argumentation with Subjective Logic

paper_content:

An Abstract Argumentation Framework (AAF) is an abstract structure consisting of a set arguments, whose origin, nature, and possible internal organisation is not specified, and by a binary relation of attack on the set of arguments, whose meaning is not specified either. Subjective logic provides a standard set of logical operators, intended for use in domains containing uncertainty. In this paper, we define an extension of AAFs in which each argument and attacks is evaluated with an opinion, by revisiting the constellations approach developed for probabilistic AAFs. In this way, different agents can merge their opinions on how much arguments and attacks are “trustworthy”, e.g., they do not represent fallacies or enthymemes. Finally, subjective logic operators can be used to fuse the belief of different possible worlds (i.e., a constellation of sub-graphs in the original AAF) containing different arguments and attacks.
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paper_title: Filtering Out Unfair Ratings in Bayesian Reputation Systems

paper_content:

The quality of a reputation system depends on the integrity of the ratings it receives as input. A fundamental problem is that a rater can rate an agent more positively or more negatively than the real experience with the agent would dictate. When ratings are provided by agents outside the control of the relying party, it is a priori impossible to know when a rater provides such unfair ratings. However, it is often the case that unfair ratings have a different statistical pattern than fair ratings. This paper uses that idea, and describes a statistical ltering technique for excluding unfair ratings, and illustrates its effectiveness through simulations.
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paper_title: Semiring-based trust evaluation for information fusion in social network services

paper_content:

As online social network services (SNS) are booming and gaining tremendous popularity, there is a sharply increasing amount of information exchange and interactions among SNS users. Taking this advantage, users in SNS make decisions via collecting and combining information from different sources (i.e. other users). However, there exists a large variance of trustworthiness among SNS populations, which is threatening the quality of the information fusion process. In such circumstances, trust relationships among users in SNS are very important in decision making as well as for the success of many SNS-based applications, e.g. recommender systems and ad targeting. An appropriate trust inference mechanism for trust evaluation is necessary in extending the knowledge base of trust opinions and tackle the issue of limited trust information due to link sparsity in social networks. In this work, we model the trust relationship among users in SNS as a 2-dimensional vector, and propose a semiring-based model for trust propagation and fusion as the building block of our trust inference framework. Specifically, in our approach, both trust and distrust (i.e., positive and negative trust) are both considered, and opinion conflict resolution is supported by our framework of trust inference.
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paper_title: URREF self-confidence in information fusion trust

paper_content:

The Uncertainty Representation and Reasoning Evaluation Framework (URREF) includes an ontology that represents concepts and criteria needed to evaluate the uncertainty management aspects of a fusion system. The URREF ontology defines self-confidence as a measure of the information credibility as evaluated by the sensor itself. The concept of confidence, which is not explicitly defined in the ontology at URREF, has been extensively explored in the literature about evaluation in information fusion systems (IFS). In this paper, we provide a discussion on confidence as it relates to the evaluation of IFS, and compare it with the existing concepts in the URREF ontology. Our goal is two-fold, since we address both the distinctions between confidence and self-confidence, as well as the implications of these differences when evaluating the impact of uncertainty to the decision-making processes supported byt the IFS. We illustrate the discussion with an example of decision making that involves signal detection theory, confusion matrix fusion, subjective logic, and proportional conflict redistribution. We argue that uncertainty can be minimized through confidence (information evidence) and self-confidence (source agent) processing, The results here seek to enrich the ongoing discussion at the ISIF's Evaluation of Techniques for Uncertainty Representation Working Group (ETURWG) on self-confidence and trust in information fusion systems design.
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paper_title: An Efficient and Versatile Approach to Trust and Reputation using Hierarchical Bayesian Modelling

paper_content:

In many dynamic open systems, autonomous agents must interact with one another to achieve their goals. Such agents may be self-interested and, when trusted to perform an action, may betray that trust by not performing the action as required. Due to the scale and dynamism of these systems, agents will often need to interact with other agents with which they have little or no past experience. Each agent must therefore be capable of assessing and identifying reliable interaction partners, even if it has no personal experience with them. To this end, we present HABIT, a Hierarchical And Bayesian Inferred Trust model for assessing how much an agent should trust its peers based on direct and third party information. This model is robust in environments in which third party information is malicious, noisy, or otherwise inaccurate. Although existing approaches claim to achieve this, most rely on heuristics with little theoretical foundation. In contrast, HABIT is based exclusively on principled statistical techniques: it can cope with multiple discrete or continuous aspects of trustee behaviour; it does not restrict agents to using a single shared representation of behaviour; it can improve assessment by using any observed correlation between the behaviour of similar trustees or information sources; and it provides a pragmatic solution to the whitewasher problem (in which unreliable agents assume a new identity to avoid bad reputation). In this paper, we describe the theoretical aspects of HABIT, and present experimental results that demonstrate its ability to predict agent behaviour in both a simulated environment, and one based on data from a real-world webserver domain. In particular, these experiments show that HABIT can predict trustee performance based on multiple representations of behaviour, and is up to twice as accurate as BLADE, an existing state-of-the-art trust model that is both statistically principled and has been previously shown to outperform a number of other probabilistic trust models.
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paper_title: The Beta Reputation System

paper_content:

Reputation systems can be used to foster good behaviour and to encourage adherence to contracts in e-commerce. Several reputation systems have been deployed in practical applications or proposed in the literature. This paper describes a new system called the beta reputation system which is based on using beta probability density functions to combine feedback and derive reputation ratings. The advantage of the beta reputation system is flexibility and simplicity as well as its foundation on the theory of statistics.
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paper_title: A Trust Based Framework for Secure Data Aggregation in Wireless Sensor Networks

paper_content:

In unattended and hostile environments, node compromise can become a disastrous threat to wireless sensor networks and introduce uncertainty in the aggregation results. A compromised node often tends to completely reveal its secrets to the adversary which in turn renders purely cryptography-based approaches vulnerable. How to secure the information aggregation process against compromised-node attacks and quantify the uncertainty existing in the aggregation results has become an important research issue. In this paper, we address this problem by proposing a trust based framework, which is rooted in sound statistics and some other distinct and yet closely coupled techniques. The trustworthiness (reputation) of each individual sensor node is evaluated by using an information theoretic concept, Kullback-Leibler (KL) distance, to identify the compromised nodes through an unsupervised learning algorithm. Upon aggregating, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As the result is being disseminated and assembled through the routes to the sink, this opinion will be propagated and regulated by Josang's belief model. Following this model, the uncertainty within the data and aggregation results can be effectively quantified throughout the network. Simulation results demonstrate that our trust based framework provides a powerful mechanism for detecting compromised nodes and reasoning about the uncertainty in the network. It further can purge false data to accomplish robust aggregation in the presence of multiple compromised nodes
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paper_title: Fusion of classifiers: A subjective logic perspective

paper_content:

This work investigates decision level fusion by extending the framework of subjective logic to account for hidden observations. Bayes' rule might suggest that decision level fusion is simply calculated as the normalized product of the class likelihoods of the various classifiers. However, this product rule suffers from a veto issue. The problem with the classical Bayes formulation is that it does not account for uncertainties inherent in the likelihoods exclaimed by the classifiers. This paper uses subjective logic as a rigorous framework to incorporate uncertainty. First, a class appearance model is introduced that roughly accounts for the disparity between training and testing conditions. Then, the subjective logic framework is expanded to account for the fact that class appearances are not directly observed. Rather, a classifier only returns the likelihood for the class appearance. Finally, the paper uses simulations to compare the new subjective logic framework to traditional classifier fusion methods in terms of classification performance and the ability to estimate the parameters of the class appearance model.
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paper_title: Trust estimation and fusion of uncertain information by exploiting consistency

paper_content:

Agents may cooperate by communicating their opinions about various phenomena. These opinions are then fused by agents and used for informed decision-making. However, fusing opinions from diverse sources is not trivial - especially in open multiagent systems - where it is not possible to ensure that the sources are honest and their opinions are not misleading. In this paper, we propose a novel approach that exploits consistencies and conflicts between personal observations and shared information to derive trust evidence for information sources. Based on the derived evidence, we describe how opinions from diverse sources can be fused. We have evaluated our approach for trust estimation and opinion fusion using a service selection scenario. Through extensive simulations, we have shown that our approach significantly outperforms the existing trust-based information fusion approaches.
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paper_title: TIDY: A trust-based approach to information fusion through diversity

paper_content:

Trust and reputation are significant components in open dynamic systems for making informed and reliable decisions. State-of-the-art information fusion models that exploit these mechanisms generally rely on reports from as many sources as possible. Situations exist, however, where seeking evidence from all possible sources is unrealistic. Querying information sources is costly especially in resource-constrained environments, in terms of time and bandwidth. In addition, reports from multiple sources expose one to the risk of double-counting evidence, introducing an extra challenge of distinguishing fact from rumour. This paper describes TIDY (Trust-based Information fusion through DiversitY), a trust-based approach to information fusion that exploits diversity among information sources in order to select a small number of candidates to query for evidence, and to minimise the effect of correlated evidence and bias. We demonstrate that reliable decisions can be reached using evidence from small groups of individuals. We show empirically that our approach is robust in contexts of variable trust in information sources, and to a degree of deception.
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paper_title: Trust-based fusion of untrustworthy information in crowdsourcing applications

paper_content:

In this paper, we address the problem of fusing untrustworthy reports provided from a crowd of observers, while simultaneously learning the trustworthiness of individuals. To achieve this, we construct a likelihood model of the users's trustworthiness by scaling the uncertainty of its multiple estimates with trustworthiness parameters. We incorporate our trust model into a fusion method that merges estimates based on the trust parameters and we provide an inference algorithm that jointly computes the fused output and the individual trustworthiness of the users based on the maximum likelihood framework. We apply our algorithm to cell tower local- isation using real-world data from the OpenSignal project and we show that it outperforms the state-of-the-art methods in both accuracy, by up to 21%, and consistency, by up to 50% of its predictions.
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paper_title: FUSE-BEE: Fusion of subjective opinions through behavior estimation

paper_content:

Information is critical in almost all decision making processes. Therefore, it is important to get the right information at the right time from the right sources. However, information sources may behave differently while providing information — i.e., they may provide unreliable, erroneous, noisy, or misleading information deliberately or unintentionally. Motivated by this observation, in this paper, we propose a statistical information fusion approach based on behavior estimation. Our approach transforms the conveyed information into more useful form by tempering them with the estimated behaviors of sources. Through extensive simulations, we have shown that our approach has a lower computational complexity, and achieves significantly low behavior estimation and fusion errors.
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paper_title: Bayesian reputation modeling in e-marketplaces sensitive to subjectivity, deception and change

paper_content:

We present a model for buying agents in e-marketplaces to interpret evaluations of sellers provided by other buying agents, known as advisors. The interpretation of seller evaluations is complicated by the inherent subjectivity of each advisor, the possibility that advisors may deliberately provide misleading evaluations to deceive competitors and the dynamic nature of seller and advisor behaviours that may naturally change seller evaluations over time. Using a Bayesian approach, we demonstrate how to cope with subjectivity, deception and change in a principled way. More specifically, by modeling seller properties and advisor evaluation functions as dynamic random variables, buyers can progressively learn a probabilistic model that naturally and "correctly" calibrates the interpretation of seller evaluations without having to resort to heuristics to explicitely detect and filter/discount unreliable seller evaluations. Our model, called BLADE, is shown empirically to achieve lower mean error in the estimation of seller properties when compared to other models for reasoning about advisor ratings of sellers in electronic maketplaces.
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paper_title: Trust revision for conflicting sources

paper_content:

Sensors and information sources can produce conflicting evidence for various reasons, including errors and deception. When conflicting evidence is received, some sources produce more accurate evidence than others with regard to the ground truth. The reliability of sources can be expressed by assigning a level of trust to each source. In this situation, multiple fusion strategies can be applied: one strategy is to directly fuse the evidence based on a priori trust in each source, another strategy is to first revise a priori trust assignments as a function of the degree of conflict, before the evidence is fused. This paper focuses on the latter approach, and describes a method for applying trust revision in case of highly conflicting evidence. The trust revision method is expressed in the formalism of subjective logic.
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paper_title: A Reputation and Knowledge Based Trust Service Platform for Trustworthy Social Internet of Things

paper_content:

The Internet of Things has attracted a plenty of research in this decade and imposed fascinating services where large numbers of heterogeneous-features entities socially collaborate together to solve complex scenarios. However, these entities need to trust each other prior to exchanging data or offering services. In this paper, we briefly present our ongoing project called Trust Service Platform, which offers trust assessment of any two entities in the Social Internet of Things to applications and services. We propose a trust model that incorporates both reputation properties as Recommendation and Reputation trust metrics; and knowledge-based property as Knowledge trust metric. For the trust service platform deployment, we propose a reputation system and a functional architecture with Trust Agent, Trust Broker and Trust Analysis and Management modules along with mechanisms and algorithms to deal with the three trust metrics. We also present a utility theory-based mechanism for trust calculation. To clarify our trust service platform, we describe the trust models and mechanisms in accordance with a trust car-sharing service. We believe this study offers the better understanding of the trust as a service in the platform and will impose many trust-related research challenges as the future work.
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paper_title: Data centric trust evaluation and prediction framework for IOT

paper_content:

Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas.
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paper_title: A Centralized Trust Management Mechanism for the Internet of Things (CTM-IoT)

paper_content:

The Internet of Things (IoT) is an extended network that allows all devices to be connected to one another over the Internet. This new network faces numerous challenges, but mainly security issues. One such issue is how the IoT’s nodes can trust each other when they are connected over the Internet. There is a lack of studies that address the issue of trust management in IoT, or that provide a fully trustworthy framework. This paper proposes and delivers a centralized trust management mechanism for IoT by adding trust modules as a feature of the central trust manager, the Super Node (SN). To deliver a comprehensive approach, the SN includes other modules which are integrated with the whole IoT Trust Management framework to provide trustworthy communication between all nodes.
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paper_title: Guarantor and reputation based trust model for Social Internet of Things

paper_content:

The addition of social networking to Internet of Things (IoT) has led to the paradigm of Social Internet of Things (SIoT). It is where digital devices called objects mimic the social behavior of their human counterparts and build up social relationships with other objects in order to provide services to the humans. One of the obstacles in realizing this idea is trust management. The most complex question in trust building is ‘How can objects trust the information provided by other objects?’ This paper proposes a new trust model based on Guarantor and Reputation for SIoT. The former requests an object to find a guarantor at an agreed commission rate in order to get service from another object; the latter uses reputation of a node to measure its trustworthiness. By simulating this model using an architecture based on real world scenarios, it was concluded that the trust model can be employed in different scenarios in SIoT and the use of penalties for malicious activity enables the model to detect and isolate malicious nodes.
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paper_title: Trust management system design for the Internet of Things: A context-aware and multi-service approach

paper_content:

This work proposes a new trust management system (TMS) for the Internet of Things (IoT). The wide majority of these systems are today bound to the assessment of trustworthiness with respect to a single function. As such, they cannot use past experiences related to other functions. Even those that support multiple functions hide this heterogeneity by regrouping all past experiences into a single metric. These restrictions are detrimental to the adaptation of TMSs to today's emerging M2M and IoT architectures, which are characterized with heterogeneity in nodes, capabilities and services. To overcome these limitations, we design a context-aware and multi-service trust management system fitting the new requirements of the IoT. Simulation results show the good performance of the proposed system and especially highlight its ability to deter a class of common attacks designed to target trust management systems.
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paper_title: Trust architecture and reputation evaluation for internet of things

paper_content:

Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and reputation evaluation. However, existing trust architectures and reputation evaluation solutions cannot be directly applied to the IoT, due to the large number of physical entities, the limited computation ability of physical entities, and the highly dynamic nature of the network. In comparison, it generally requires a general and flexible architecture to manage trust in such a dynamic environment as IoT. In this paper, we present IoTrust, a trust architecture that integrates Soft Defined Network (SDN) in IoT, and a cross-layer authorization protocol based on IoTrust. IoTrust and the protocol together provide a new insight for research on trust management in the IoT. For trust establishment, we further propose a Behavior-based Reputation Evaluation Scheme for the Node (BES) and an Organization Reputation Evaluation Scheme (ORES). Both our theoretical analysis and simulation results validate the efficiency of BES and ORES.
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paper_title: TMCoI-SIOT: A trust management system based on communities of interest for the social Internet of Things

paper_content:

We propose a trust management system (TMS) for the social Internet of things (SIOT) called TMCoI-SIOT. The proposed system integrates numerous factors such as direct and indirect trust; transaction factors and social modeling of trust. The novelty of our approach can be summed up in three aspects. The first aspect concerns the network architecture which is seen as a set of nodes groups called community of interest (CoI). Each community nodes shares the same interests and is headed by an administrator (admin. The second aspect is the trust management system that prevents On-Off attacks. The third aspect concerns the trust prediction method that uses the Kalman filter technique in order to estimate nodes behaviors and prevent possible attacks. We prove the effectiveness of the proposed system by simulation against TMS attacks.
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paper_title: Dynamic trust management for internet of things applications

paper_content:

We propose a dynamic trust management protocol for Internet of Things (IoT) systems to deal with misbehaving nodes whose status or behavior may change dynamically. We consider an IoT system being deployed in a smart community where each node autonomously performs trust evaluation. We provide a formal treatment of the convergence, accuracy, and resilience properties of our dynamic trust management protocol and validate these desirable properties through simulation. We demonstrate the effectiveness of our dynamic trust management protocol with a trust-based service composition application in IoT environments. Our results indicate that trust-based service composition significantly outperforms non-trust-based service composition and approaches the maximum achievable performance based on ground truth status. Furthermore, our dynamic trust management protocol is capable of adaptively adjusting the best trust parameter setting in response to dynamically changing environments to maximize application performance.
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paper_title: Decentralizing Privacy: Using Blockchain to Protect Personal Data

paper_content:

The recent increase in reported incidents of surveillance and security breaches compromising users' privacy call into question the current model, in which third-parties collect and control massive amounts of personal data. Bit coin has demonstrated in the financial space that trusted, auditable computing is possible using a decentralized network of peers accompanied by a public ledger. In this paper, we describe a decentralized personal data management system that ensures users own and control their data. We implement a protocol that turns a block chain into an automated access-control manager that does not require trust in a third party. Unlike Bit coin, transactions in our system are not strictly financial -- they are used to carry instructions, such as storing, querying and sharing data. Finally, we discuss possible future extensions to block chains that could harness them into a well-rounded solution for trusted computing problems in society.
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paper_title: M2M-REP: Reputation system for machines in the internet of things

paper_content:

Abstract In the age of IoT (Internet of Things), Machine-to-Machine (M2M) communication has gained significant popularity over the last few years. M2M communication systems may have a large number of autonomous connected devices that provide services without human involvement. Interacting with compromised, infected and malicious machines can bring damaging consequences in the form of network outage, machine failure, data integrity, and financial loss. Hence, users first need to evaluate the trustworthiness of machines prior to interacting with them. This can be realized by using a reputation system, which evaluates the trustworthiness of machines by utilizing the feedback collected from the users of the machines. The design of a reliable reputation system for the distributed M2M communication network should preserve user privacy and have low computation and communication overheads. To address these challenges, we propose an M2M-REP System (Machine to Machine REPutation), a privacy-preserving reputation system for evaluating the trustworthiness of autonomous machines in the M2M network. The system computes global reputation scores of machines while maintaining privacy of the individual participant score by using secure multi-party computation techniques. The M2M-REP system ensures correctness, security and privacy properties under the malicious adversarial model, and allows public verifiability without relying on a centralized trusted system. We implement a prototype of our system and evaluate the system performance in terms of the computation and bandwidth overhead.
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paper_title: An Efficient Architecture for Trust Management in IoE Based Systems of Systems

paper_content:

Internet of Every things (IoE) is a network that integrates a variety of heterogeneous nodes, such as connected portable devices, connected cars, smart home appliances, humans, etc. to Internet. The constituents of IoE are heterogeneous, distributed by nature and also autonomous in most of cases, which meet the criteria of what we call Systems of Systems (SoS). These smart objects communicate and collaborate between each other in dynamic environments which are subject to several security attacks. In this paper, we propose a hierarchical based blockchain trust management architecture with mobility support in highly distributed IoE based Systems of Systems. This architecture deals efficiently with scalability issues. It allows smart objects to disseminate the trustworthiness of the service providers they interact with them to the blockchain. This later makes the access to this information possible from anywhere and ensures a global view of trustworthiness information. Thanks to the blockchain technology, our architecture outperforms the existing trust management solutions especially in terms of scalability and mobility support.
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paper_title: Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

paper_content:

An Internet of Things (IoT) system connects a large amount of tags, sensors, and mobile devices to facilitate information sharing, enabling a variety of attractive applications. It challenges the design and evaluation of IoT systems to meet the scalability, compatibility, extendibility, dynamic adaptability and resiliency requirements. In this paper, we design and evaluate a scalable, adaptive and survivable trust management protocol in dynamic IoT environments. Recognizing that entities in an IoT system are connected through social networks of entity owners, we consider a community of interest (CoI) based social IoT where nodes form into communities of interest. Given inter-CoI vs. intra-CoI social connections among entity owners as input, we identify best trust protocol settings for achieving convergence, accuracy, dynamic adaptability and resiliency properties in the presence of dynamically changing conditions and malicious nodes performing trust-related attacks. For scalability, we consider a design by which a node only keeps trust information of a subset of nodes meeting its interest and performs minimum computation to update trust. We validate our design by extensive simulation considering both limited and ideal (unlimited) storage space. The results demonstrate that our trust management protocol using limited storage space achieves a similar performance level compared with the one under ideal storage space, and a newly joining node can quickly build up trust towards other nodes with desirable accuracy and convergence behavior.
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paper_title: On blockchain and its integration with IoT. Challenges and opportunities

paper_content:

Abstract In the Internet of Things (IoT) vision, conventional devices become smart and autonomous. This vision is turning into a reality thanks to advances in technology, but there are still challenges to address, particularly in the security domain e.g., data reliability. Taking into account the predicted evolution of the IoT in the coming years, it is necessary to provide confidence in this huge incoming information source. Blockchain has emerged as a key technology that will transform the way in which we share information. Building trust in distributed environments without the need for authorities is a technological advance that has the potential to change many industries, the IoT among them. Disruptive technologies such as big data and cloud computing have been leveraged by IoT to overcome its limitations since its conception, and we think blockchain will be one of the next ones. This paper focuses on this relationship, investigates challenges in blockchain IoT applications, and surveys the most relevant work in order to analyze how blockchain could potentially improve the IoT.
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paper_title: A Mobile Cloud Hierarchical Trust Management Protocol for IoT Systems

paper_content:

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust management protocol called IoT-HiTrust for large-scale IoT systems. Our mobile cloud hierarchical trust management protocol allows an IoT device to report its service experiences and query the trustworthiness of another IoT device for service composition and selection following a simple localized report-and-query paradigm. We verify IoT-HiTrust's conver-gence, accuracy, and resiliency properties against self-promotion, discriminatory, bad-mouthing, ballot-stuffing, and opportunistic service attacks despite intermittent network disconnection to the cloud.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: A Mobile Cloud Hierarchical Trust Management Protocol for IoT Systems

paper_content:

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust management protocol called IoT-HiTrust for large-scale IoT systems. Our mobile cloud hierarchical trust management protocol allows an IoT device to report its service experiences and query the trustworthiness of another IoT device for service composition and selection following a simple localized report-and-query paradigm. We verify IoT-HiTrust's conver-gence, accuracy, and resiliency properties against self-promotion, discriminatory, bad-mouthing, ballot-stuffing, and opportunistic service attacks despite intermittent network disconnection to the cloud.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: Trust-Based Service Management for Social Internet of Things Systems

paper_content:

A social internet of things (IoT) system can be viewed as a mix of traditional peer-to-peer networks and social networks, where “things” autonomously establish social relationships according to the owners’ social networks, and seek trusted “things” that can provide services needed when they come into contact with each other opportunistically. We propose and analyze the design notion of adaptive trust management for social IoT systems in which social relationships evolve dynamically among the owners of IoT devices. We reveal the design tradeoff between trust convergence versus trust fluctuation in our adaptive trust management protocol design. With our adaptive trust management protocol, a social IoT application can adaptively choose the best trust parameter settings in response to changing IoT social conditions such that not only trust assessment is accurate but also the application performance is maximized. We propose a table-lookup method to apply the analysis results dynamically and demonstrate the feasibility of our proposed adaptive trust management scheme with two real-world social IoT service composition applications.
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paper_title: A Survey on Trust Management for Internet of Things

paper_content:

Internet of Things (IoT) is going to create a world where physical objects are seamlessly integrated into information networks in order to provide advanced and intelligent services for human-beings. Trust management plays an important role in IoT for reliable data fusion and mining, qualified services with context-awareness, and enhanced user privacy and information security. It helps people overcome perceptions of uncertainty and risk and engages in user acceptance and consumption on IoT services and applications. However, current literature still lacks a comprehensive study on trust management in IoT. In this paper, we investigate the properties of trust, propose objectives of IoT trust management, and provide a survey on the current literature advances towards trustworthy IoT. Furthermore, we discuss unsolved issues, specify research challenges and indicate future research trends by proposing a research model for holistic trust management in IoT.
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paper_title: Context-Aware Trustworthy Service Evaluation in Social Internet of Things

paper_content:

In Social Internet of Things (SIoT) environments, a large number of users and Internet of Things (IoT) based devices are connected to each other, so that they can share SIoT-based services. IoT-based devices establish social relations with each other according to the social relations of their owners in Online Social Networks (OSNs). In such an environment, a big challenge is how to provide trustworthy service evaluation. Currently, the prevalent trust management mechanisms consider QoS-based trust and social-relation based trust mechanisms in evaluating the trustworthiness of service providers. However, the existing trust management mechanisms in SIoT environments do not consider the different contexts of trust. Therefore, dishonest SIoT devices, based on their owners’ social relations, can succeed in advertising low-quality services or exploiting maliciously provided services. In this paper, we first propose three contexts of trust in SIoT environments including the status and environment (time and location) of devices, and the types of tasks. Then, we propose a novel Mutual Context-aware Trustworthy Service Evaluation (MCTSE) model. The experiments demonstrate that our proposed contextual trust evaluation model can effectively differentiate honest and dishonest devices and provide a high success rate in selecting the most trustworthy services and providing high resilience against different attacks from dishonest devices.
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paper_title: Trust Management for SOA-Based IoT and Its Application to Service Composition

paper_content:

A future Internet of Things (IoT) system will connect the physical world into cyberspace everywhere and everything via billions of smart objects. On the one hand, IoT devices are physically connected via communication networks. The service oriented architecture (SOA) can provide interoperability among heterogeneous IoT devices in physical networks. On the other hand, IoT devices are virtually connected via social networks. In this paper we propose adaptive and scalable trust management to support service composition applications in SOA-based IoT systems. We develop a technique based on distributed collaborative filtering to select feedback using similarity rating of friendship, social contact, and community of interest relationships as the filter. Further we develop a novel adaptive filtering technique to determine the best way to combine direct trust and indirect trust dynamically to minimize convergence time and trust estimation bias in the presence of malicious nodes performing opportunistic service and collusion attacks. For scalability, we consider a design by which a capacity-limited node only keeps trust information of a subset of nodes of interest and performs minimum computation to update trust. We demonstrate the effectiveness of our proposed trust management through service composition application scenarios with a comparative performance analysis against EigenTrust and PeerTrust.
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paper_title: Dynamic trust management for internet of things applications

paper_content:

We propose a dynamic trust management protocol for Internet of Things (IoT) systems to deal with misbehaving nodes whose status or behavior may change dynamically. We consider an IoT system being deployed in a smart community where each node autonomously performs trust evaluation. We provide a formal treatment of the convergence, accuracy, and resilience properties of our dynamic trust management protocol and validate these desirable properties through simulation. We demonstrate the effectiveness of our dynamic trust management protocol with a trust-based service composition application in IoT environments. Our results indicate that trust-based service composition significantly outperforms non-trust-based service composition and approaches the maximum achievable performance based on ground truth status. Furthermore, our dynamic trust management protocol is capable of adaptively adjusting the best trust parameter setting in response to dynamically changing environments to maximize application performance.
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paper_title: RpR: A Trust Computation Model for Social Internet of Things

paper_content:

Social Internet of Things (SIoT) is an evolutionary idea which combines traditional IoT models with social network paradigms. "Objects" in SIoT formulate social relationships with other "trusted objects" according to the relationships of their owners which deliver trustworthy services on request. From our trust platform concept to identify vital trust metrics, attributes, we propose a Recommendations plus Reputations based Trust Computational Model (RpR) that enables objects in SIoT to build associations in a trustworthy manner. A numerical model is developed to estimate trust of each object based on Recommendation, Reputation parameters. Next, both estimates are merged together, a robust algorithm is proposed. Finally, we demonstrate, validate the usefulness of RpR over prior approaches through simulations, analysis. The aim of our approach is to facilitate accurate modeling of trustworthiness in distributed SIoT environments.
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paper_title: SIoT: Giving a Social Structure to the Internet of Things

paper_content:

The actual development of the Internet of Things (IoT) needs major issues related to things' service discovery and composition to be addressed. This paper proposes a possible approach to solve such issues. We introduce a novel paradigm of "social network of intelligent objects", namely the Social Internet of Things (SIoT), based on the notion of social relationships among objects. Following the definition of a possible social structure among objects, a preliminary architecture for the implementation of SIoT is presented. Through the SIoT paradigm, the capability of humans and devices to discover, select, and use objects with their services in the IoT is augmented. Besides, a level of trustworthiness is enabled to steer the interaction among the billions of objects which will crowd the future IoT.
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paper_title: A Reputation and Knowledge Based Trust Service Platform for Trustworthy Social Internet of Things

paper_content:

The Internet of Things has attracted a plenty of research in this decade and imposed fascinating services where large numbers of heterogeneous-features entities socially collaborate together to solve complex scenarios. However, these entities need to trust each other prior to exchanging data or offering services. In this paper, we briefly present our ongoing project called Trust Service Platform, which offers trust assessment of any two entities in the Social Internet of Things to applications and services. We propose a trust model that incorporates both reputation properties as Recommendation and Reputation trust metrics; and knowledge-based property as Knowledge trust metric. For the trust service platform deployment, we propose a reputation system and a functional architecture with Trust Agent, Trust Broker and Trust Analysis and Management modules along with mechanisms and algorithms to deal with the three trust metrics. We also present a utility theory-based mechanism for trust calculation. To clarify our trust service platform, we describe the trust models and mechanisms in accordance with a trust car-sharing service. We believe this study offers the better understanding of the trust as a service in the platform and will impose many trust-related research challenges as the future work.
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paper_title: A scheme of access service recommendation for the Social Internet of Things

paper_content:

The rapid increase in the complexity and the extent of personalization of services in the Internet of Things IoT has led to a greater demand for frequent collaboration among heterogeneous devices. Moreover, with the inseparable relations between human and devices, the paradigm of Social IoT SIoT is gaining popularity in recent years. How to effectively facilitate the access to quality services and credible devices in large-scale networks via defining, establishing, and managing social architectures among things has become a critical issue. In this paper, a scheme of access service recommendation for the SIoT is presented with the understanding of inherent constraints and factors that influence the security and stability of IoT networks. In which, timeliness properties are considered in each transaction for dynamic performance enhancements. With the benefits of promoting service discovery and composition, social relationships among things are introduced in the proposed scheme. An energy-aware mechanism is also utilized as a restrictive factor in trustworthiness evaluation. Finally, the recommendation is based not only on the past performance but also on the social relationship and the energy status of nodes. Simulation experiments demonstrate the effectiveness and benefits of our scheme from three aspects including rating accuracy, dynamic behavior, and network stability. Copyright © 2015 John Wiley & Sons, Ltd.
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paper_title: Trust management for the internet of things and its application to service composition

paper_content:

The Internet of Things (IoT) integrates a large amount of everyday life devices from heterogeneous network environments, bringing a great challenge into security and reliability management. Recognizing that the smart objects in IoT are most likely human-carried or human-operated devices, we propose a scalable trust management protocol for IoT, with the emphasis on social relationships. We consider multiple trust properties including honesty, cooperativeness, and community-interest to account for social interaction. Each node performs trust evaluation towards a limited set of devices of its interest only. The trust management protocol is event-driven upon the occurrence of a social encounter or interaction event, and trust is aggregated using both direct observations and indirect recommendations. We analyze the effect of trust parameters on trust assessment accuracy and trust convergence time. Our results show that there exists a trade-off between trust assessment accuracy vs. trust convergence time in the presence of false recommendations attacks performed by malicious nodes. We demonstrate the effectiveness of the proposed trust management protocol with a trust-based service composition application. Our results indicate that trust-based service composition significantly outperforms non-trust-based (random) service composition and its performance approaches the maximum achievable performance with global knowledge.
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paper_title: Guarantor and reputation based trust model for Social Internet of Things

paper_content:

The addition of social networking to Internet of Things (IoT) has led to the paradigm of Social Internet of Things (SIoT). It is where digital devices called objects mimic the social behavior of their human counterparts and build up social relationships with other objects in order to provide services to the humans. One of the obstacles in realizing this idea is trust management. The most complex question in trust building is ‘How can objects trust the information provided by other objects?’ This paper proposes a new trust model based on Guarantor and Reputation for SIoT. The former requests an object to find a guarantor at an agreed commission rate in order to get service from another object; the latter uses reputation of a node to measure its trustworthiness. By simulating this model using an architecture based on real world scenarios, it was concluded that the trust model can be employed in different scenarios in SIoT and the use of penalties for malicious activity enables the model to detect and isolate malicious nodes.
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paper_title: A subjective model for trustworthiness evaluation in the social Internet of Things

paper_content:

The integration of social networking concepts into the Internet of Things (IoT) has led to the so called Social Internet of Things (SIoT) paradigm, according to which the objects are capable of establishing social relationships in an autonomous way with respect to their owners. The benefits are those of improving scalability in information/service discovery when the SIoT is made of huge numbers of heterogeneous nodes, similarly to what happens with social networks among humans. In this paper we focus on the problem of understanding how the information provided by the other members of the SIoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define a subjective model for the management of trustworthiness which builds upon the solutions proposed for P2P networks. Each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the common friends with the potential service providers. We employ a feedback system and we combine the credibility and centrality of the nodes to evaluate the trust level. Preliminary simulations show the benefits of the proposed model towards the isolation of almost any malicious node in the network.
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paper_title: Trustworthiness Management in the Social Internet of Things

paper_content:

The integration of social networking concepts into the Internet of things has led to the Social Internet of Things (SIoT) paradigm, according to which objects are capable of establishing social relationships in an autonomous way with respect to their owners with the benefits of improving the network scalability in information/service discovery. Within this scenario, we focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. In the subjective model each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the friends in common with the potential service providers. In the objective model, the information about each node is distributed and stored making use of a distributed hash table structure so that any node can make use of the same information. Simulations show how the proposed models can effectively isolate almost any malicious nodes in the network at the expenses of an increase in the network traffic for feedback exchange.
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paper_title: TRM-IoT: A trust management model based on fuzzy reputation for internet of things

paper_content:

Since a large scale Wireless Sensor Network (WSN) is to be completely ::: integrated into Internet as a core part of Internet of Things (IoT) or Cyber ::: Physical System (CPS), it is necessary to consider various security ::: challenges that come with IoT/CPS, such as the detection of malicious ::: attacks. Sensors or sensor embedded things may establish direct communication ::: between each other using 6LoWPAN protocol. A trust and reputation model is ::: recognized as an important approach to defend a large distributed sensor ::: networks in IoT/CPS against malicious node attacks, since trust establishment ::: mechanisms can stimulate collaboration among distributed computing and ::: communication entities, facilitate the detection of untrustworthy entities, ::: and assist decision-making process of various protocols. In this paper, based ::: on in-depth understanding of trust establishment process and quantitative ::: comparison among trust establishment methods, we present a trust and ::: reputation model TRM-IoT to enforce the cooperation between things in a ::: network of IoT/CPS based on their behaviors. The accuracy, robustness and ::: lightness of the proposed model is validated through a wide set of ::: simulations.
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paper_title: A Distributed Trust Management Mechanism for the Internet of Things Using a Multi-Service Approach

paper_content:

In the Internet of Things (IoT) heterogeneous devices can cooperate and communicate to provide or require determined services. A multi-service IoT is vulnerable to many types of malicious attacks. A trust management scheme is a strategy to establish trust between devices. In this work we propose a distributed trust management model for IoT using direct and indirect observations. The trust of a node is computed by the service quality and recommendations from neighbors. The nodes locally compute the trust of their neighbors, without the need of a central entity. We implemented the proposed strategy in the Cooja simulator of the Contiki operating system to analyze the performance of the trust model. We performed simulations using different number of malicious nodes performing the bad mouthing attack. Simulation results show the trust management scheme is able to detect malicious nodes in the network.
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paper_title: Trust management mechanism for Internet of Things

paper_content:

Trust management has been proven to be a useful technology for providing security service and as a consequence has been used in many applications such as P2P, Grid, ad hoc network and so on. However, few researches about trust mechanism for Internet of Things (IoT) could be found in the literature, though we argue that considerable necessity is held for applying trust mechanism to IoT. In this paper, we establish a formal trust management control mechanism based on architecture modeling of IoT. We decompose the IoT into three layers, which are sensor layer, core layer and application layer, from aspects of network composition of IoT. Each layer is controlled by trust management for special purpose: self-organized, affective routing and multi-service respectively. And the final decision-making is performed by service requester according to the collected trust information as well as requester' policy. Finally, we use a formal semantics-based and fuzzy set theory to realize all above trust mechanism, the result of which provides a general framework for the development of trust models of IoT.
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paper_title: Mitigating On-Off Attacks in the Internet of Things Using a Distributed Trust Management Scheme

paper_content:

In the Internet of Things (IoT), physical objects are able to provide or require determined services. The purpose of this work is to identify malicious behavior of nodes and prevent possible On-Off attacks to a multiservice IoT. The proposed trust management model uses direct information generated from direct communication with the nodes to evaluate trust between nodes. This distributed approach allows nodes to be completely autonomous in making decisions about the behavior of other nodes. We perform network simulations using Contiki-OS to analyze the performance of the proposed trust model. Simulation results show effectiveness against On-Off attacks and also a good performance to recognize malicious nodes in the network.
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paper_title: Trust management system design for the Internet of Things: A context-aware and multi-service approach

paper_content:

This work proposes a new trust management system (TMS) for the Internet of Things (IoT). The wide majority of these systems are today bound to the assessment of trustworthiness with respect to a single function. As such, they cannot use past experiences related to other functions. Even those that support multiple functions hide this heterogeneity by regrouping all past experiences into a single metric. These restrictions are detrimental to the adaptation of TMSs to today's emerging M2M and IoT architectures, which are characterized with heterogeneity in nodes, capabilities and services. To overcome these limitations, we design a context-aware and multi-service trust management system fitting the new requirements of the IoT. Simulation results show the good performance of the proposed system and especially highlight its ability to deter a class of common attacks designed to target trust management systems.
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paper_title: Distributed Trust Management Mechanism for the Internet of Things

paper_content:

Trust management provides a potential solution for the security issues of distributed networks. However, there are rare researches about the trust mechanism for IoT in the literature. A new distributed trust management mechanism for IoT is established in this paper. Firstly, we extract three basic elements-service, decision-making and self-organizing, of trust management from the investigated trust solutions. Then, based on a service model, we establish a trust management frame-work for the layered IoT, which is decomposed into three layers: sensor layer, core layer and application layer. Finally, we use fuzzy set theory and formal semantics-based language to perform the layered trust mechanism. The proposed trust conception, layered service model and formal method provide a general framework for the study of trust management for the IoT, and further provide a significant reference for the development of sound trust models for IoT.
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paper_title: A fuzzy approach to trust based access control in internet of things

paper_content:

In the Internet of thing (IoT), the activities of daily life are supported by a multitude of heterogeneous, loosely coupled ubiquitous devices. Traditional access control model are not suitable to the nomadic, decentralized and dynamic scenarios in the IoT where identities are not known in advance. This makes the trust management in IoT more promising to address the access control issues .This paper present a Fuzzy approach to the Trust Based Access Control (FBAC) with the notion of trust levels for identity management. The presented fuzzy approach for trust calculations deals with the linguistic information of devices to address access control in the IoT. The simulation result shows that the fuzzy approach for trust based access control guarantees scalability ad it is energy efficient. This paper also proposes FTBAC framework or trust based dynamic access control in distributed IoT. FTBAC framework i a flexible and scalable a increasing number o devices do not affect the functioning and performance.
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paper_title: M2M-REP: Reputation system for machines in the internet of things

paper_content:

Abstract In the age of IoT (Internet of Things), Machine-to-Machine (M2M) communication has gained significant popularity over the last few years. M2M communication systems may have a large number of autonomous connected devices that provide services without human involvement. Interacting with compromised, infected and malicious machines can bring damaging consequences in the form of network outage, machine failure, data integrity, and financial loss. Hence, users first need to evaluate the trustworthiness of machines prior to interacting with them. This can be realized by using a reputation system, which evaluates the trustworthiness of machines by utilizing the feedback collected from the users of the machines. The design of a reliable reputation system for the distributed M2M communication network should preserve user privacy and have low computation and communication overheads. To address these challenges, we propose an M2M-REP System (Machine to Machine REPutation), a privacy-preserving reputation system for evaluating the trustworthiness of autonomous machines in the M2M network. The system computes global reputation scores of machines while maintaining privacy of the individual participant score by using secure multi-party computation techniques. The M2M-REP system ensures correctness, security and privacy properties under the malicious adversarial model, and allows public verifiability without relying on a centralized trusted system. We implement a prototype of our system and evaluate the system performance in terms of the computation and bandwidth overhead.
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paper_title: Quantifying trust relationships based on real-world social interactions

paper_content:

Deriving trust relationships from real-world social interactions may contribute significant information towards social behaviour understanding. The level of trust among people constitutes an insightful parameter for describing the social context but also an important measure for security and privacy in pervasive systems. Current works for deriving trust relationships either consider only on-line social networks to create trust networks or focus on users' on-line social interactions. This article presents MobTrust, an opportunistic sensing system that derives and quantifies trust relationships among people through smartphones based on the detected real-world social interactions. A real-world social graph is derived from users' daily social interactions by also considering snapshots of their social relation. A hybrid model was developed to quantify users' trust relationships based on the extracted real-world social graph, the estimated social relations and the contextual information provided by the detected social interactions. As a proof of concept, a real-world evaluation of the system is performed. The evaluation shows that MobTrust can reliably derive and quantify trust relationships, having as such the potential of empowering a variety of real-world scenarios that can leverage such knowledge.
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paper_title: A Mobile Cloud Hierarchical Trust Management Protocol for IoT Systems

paper_content:

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust management protocol called IoT-HiTrust for large-scale IoT systems. Our mobile cloud hierarchical trust management protocol allows an IoT device to report its service experiences and query the trustworthiness of another IoT device for service composition and selection following a simple localized report-and-query paradigm. We verify IoT-HiTrust's conver-gence, accuracy, and resiliency properties against self-promotion, discriminatory, bad-mouthing, ballot-stuffing, and opportunistic service attacks despite intermittent network disconnection to the cloud.
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paper_title: Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions

paper_content:

Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fueled by the recent adaptation of a variety of enabling wireless technologies such as RFID tags and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a Cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A Cloud implementation using Aneka, which is based on interaction of private and public Clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.
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paper_title: Dynamic trust management for internet of things applications

paper_content:

We propose a dynamic trust management protocol for Internet of Things (IoT) systems to deal with misbehaving nodes whose status or behavior may change dynamically. We consider an IoT system being deployed in a smart community where each node autonomously performs trust evaluation. We provide a formal treatment of the convergence, accuracy, and resilience properties of our dynamic trust management protocol and validate these desirable properties through simulation. We demonstrate the effectiveness of our dynamic trust management protocol with a trust-based service composition application in IoT environments. Our results indicate that trust-based service composition significantly outperforms non-trust-based service composition and approaches the maximum achievable performance based on ground truth status. Furthermore, our dynamic trust management protocol is capable of adaptively adjusting the best trust parameter setting in response to dynamically changing environments to maximize application performance.
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paper_title: M2M-REP: Reputation system for machines in the internet of things

paper_content:

Abstract In the age of IoT (Internet of Things), Machine-to-Machine (M2M) communication has gained significant popularity over the last few years. M2M communication systems may have a large number of autonomous connected devices that provide services without human involvement. Interacting with compromised, infected and malicious machines can bring damaging consequences in the form of network outage, machine failure, data integrity, and financial loss. Hence, users first need to evaluate the trustworthiness of machines prior to interacting with them. This can be realized by using a reputation system, which evaluates the trustworthiness of machines by utilizing the feedback collected from the users of the machines. The design of a reliable reputation system for the distributed M2M communication network should preserve user privacy and have low computation and communication overheads. To address these challenges, we propose an M2M-REP System (Machine to Machine REPutation), a privacy-preserving reputation system for evaluating the trustworthiness of autonomous machines in the M2M network. The system computes global reputation scores of machines while maintaining privacy of the individual participant score by using secure multi-party computation techniques. The M2M-REP system ensures correctness, security and privacy properties under the malicious adversarial model, and allows public verifiability without relying on a centralized trusted system. We implement a prototype of our system and evaluate the system performance in terms of the computation and bandwidth overhead.
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paper_title: Data centric trust evaluation and prediction framework for IOT

paper_content:

Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas.
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paper_title: A Centralized Trust Management Mechanism for the Internet of Things (CTM-IoT)

paper_content:

The Internet of Things (IoT) is an extended network that allows all devices to be connected to one another over the Internet. This new network faces numerous challenges, but mainly security issues. One such issue is how the IoT’s nodes can trust each other when they are connected over the Internet. There is a lack of studies that address the issue of trust management in IoT, or that provide a fully trustworthy framework. This paper proposes and delivers a centralized trust management mechanism for IoT by adding trust modules as a feature of the central trust manager, the Super Node (SN). To deliver a comprehensive approach, the SN includes other modules which are integrated with the whole IoT Trust Management framework to provide trustworthy communication between all nodes.
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paper_title: An Efficient Architecture for Trust Management in IoE Based Systems of Systems

paper_content:

Internet of Every things (IoE) is a network that integrates a variety of heterogeneous nodes, such as connected portable devices, connected cars, smart home appliances, humans, etc. to Internet. The constituents of IoE are heterogeneous, distributed by nature and also autonomous in most of cases, which meet the criteria of what we call Systems of Systems (SoS). These smart objects communicate and collaborate between each other in dynamic environments which are subject to several security attacks. In this paper, we propose a hierarchical based blockchain trust management architecture with mobility support in highly distributed IoE based Systems of Systems. This architecture deals efficiently with scalability issues. It allows smart objects to disseminate the trustworthiness of the service providers they interact with them to the blockchain. This later makes the access to this information possible from anywhere and ensures a global view of trustworthiness information. Thanks to the blockchain technology, our architecture outperforms the existing trust management solutions especially in terms of scalability and mobility support.
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paper_title: Guarantor and reputation based trust model for Social Internet of Things

paper_content:

The addition of social networking to Internet of Things (IoT) has led to the paradigm of Social Internet of Things (SIoT). It is where digital devices called objects mimic the social behavior of their human counterparts and build up social relationships with other objects in order to provide services to the humans. One of the obstacles in realizing this idea is trust management. The most complex question in trust building is ‘How can objects trust the information provided by other objects?’ This paper proposes a new trust model based on Guarantor and Reputation for SIoT. The former requests an object to find a guarantor at an agreed commission rate in order to get service from another object; the latter uses reputation of a node to measure its trustworthiness. By simulating this model using an architecture based on real world scenarios, it was concluded that the trust model can be employed in different scenarios in SIoT and the use of penalties for malicious activity enables the model to detect and isolate malicious nodes.
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paper_title: Trust management system design for the Internet of Things: A context-aware and multi-service approach

paper_content:

This work proposes a new trust management system (TMS) for the Internet of Things (IoT). The wide majority of these systems are today bound to the assessment of trustworthiness with respect to a single function. As such, they cannot use past experiences related to other functions. Even those that support multiple functions hide this heterogeneity by regrouping all past experiences into a single metric. These restrictions are detrimental to the adaptation of TMSs to today's emerging M2M and IoT architectures, which are characterized with heterogeneity in nodes, capabilities and services. To overcome these limitations, we design a context-aware and multi-service trust management system fitting the new requirements of the IoT. Simulation results show the good performance of the proposed system and especially highlight its ability to deter a class of common attacks designed to target trust management systems.
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paper_title: Scalable, adaptive and survivable trust management for community of interest based Internet of Things systems

paper_content:

An Internet of Things (IoT) system connects a large amount of tags, sensors, and mobile devices to facilitate information sharing, enabling a variety of attractive applications. It challenges the design and evaluation of IoT systems to meet the scalability, compatibility, extendibility, dynamic adaptability and resiliency requirements. In this paper, we design and evaluate a scalable, adaptive and survivable trust management protocol in dynamic IoT environments. Recognizing that entities in an IoT system are connected through social networks of entity owners, we consider a community of interest (CoI) based social IoT where nodes form into communities of interest. Given inter-CoI vs. intra-CoI social connections among entity owners as input, we identify best trust protocol settings for achieving convergence, accuracy, dynamic adaptability and resiliency properties in the presence of dynamically changing conditions and malicious nodes performing trust-related attacks. For scalability, we consider a design by which a node only keeps trust information of a subset of nodes meeting its interest and performs minimum computation to update trust. We validate our design by extensive simulation considering both limited and ideal (unlimited) storage space. The results demonstrate that our trust management protocol using limited storage space achieves a similar performance level compared with the one under ideal storage space, and a newly joining node can quickly build up trust towards other nodes with desirable accuracy and convergence behavior.
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paper_title: Autonomic Trust Management for a Component-Based Software System

paper_content:

Trust plays an important role in a software system, especially when, the system is component based and varied due to component joining and leaving. How to manage trust in such a system is crucial for embedded devices, such as mobile phones. This paper presents a trust management solution that can manage trust adaptively in a component based software (CBS) system. We develop a formal trust model to specify, evaluate and set up trust relationships that exist among system entities. We further present an autonomic trust management architecture that adopts a number of algorithms for trust assessment and maintenance during component execution. These algorithms use recent advances in Subjective Logic to ensure the management of trust within the CBS system.
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paper_title: A Secure IoT Service Architecture With an Efficient Balance Dynamics Based on Cloud and Edge Computing

paper_content:

The Internet of Things (IoT)-Cloud combines the IoT and cloud computing, which not only enhances the IoT’s capability but also expands the scope of its applications. However, it exhibits significant security and efficiency problems that must be solved. Internal attacks account for a large fraction of the associated security problems, however, traditional security strategies are not capable of addressing these attacks effectively. Moreover, as repeated/similar service requirements become greater in number, the efficiency of IoT-Cloud services is seriously affected. In this paper, a novel architecture that integrates a trust evaluation mechanism and service template with a balance dynamics based on cloud and edge computing is proposed to overcome these problems. In this architecture, the edge network and the edge platform are designed in such a way as to reduce resource consumption and ensure the extensibility of trust evaluation mechanism, respectively. To improve the efficiency of IoT-Cloud services, the service parameter template is established in the cloud and the service parsing template is established in the edge platform. Moreover, the edge network can assist the edge platform in establishing service parsing templates based on the trust evaluation mechanism and meet special service requirements. The experimental results illustrate that this edge-based architecture can improve both the security and efficiency of IoT-Cloud systems.
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paper_title: A Mobile Cloud Hierarchical Trust Management Protocol for IoT Systems

paper_content:

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust management protocol called IoT-HiTrust for large-scale IoT systems. Our mobile cloud hierarchical trust management protocol allows an IoT device to report its service experiences and query the trustworthiness of another IoT device for service composition and selection following a simple localized report-and-query paradigm. We verify IoT-HiTrust's conver-gence, accuracy, and resiliency properties against self-promotion, discriminatory, bad-mouthing, ballot-stuffing, and opportunistic service attacks despite intermittent network disconnection to the cloud.
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paper_title: Context-Aware Trustworthy Service Evaluation in Social Internet of Things

paper_content:

In Social Internet of Things (SIoT) environments, a large number of users and Internet of Things (IoT) based devices are connected to each other, so that they can share SIoT-based services. IoT-based devices establish social relations with each other according to the social relations of their owners in Online Social Networks (OSNs). In such an environment, a big challenge is how to provide trustworthy service evaluation. Currently, the prevalent trust management mechanisms consider QoS-based trust and social-relation based trust mechanisms in evaluating the trustworthiness of service providers. However, the existing trust management mechanisms in SIoT environments do not consider the different contexts of trust. Therefore, dishonest SIoT devices, based on their owners’ social relations, can succeed in advertising low-quality services or exploiting maliciously provided services. In this paper, we first propose three contexts of trust in SIoT environments including the status and environment (time and location) of devices, and the types of tasks. Then, we propose a novel Mutual Context-aware Trustworthy Service Evaluation (MCTSE) model. The experiments demonstrate that our proposed contextual trust evaluation model can effectively differentiate honest and dishonest devices and provide a high success rate in selecting the most trustworthy services and providing high resilience against different attacks from dishonest devices.
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paper_title: A formal definition for trust in distributed systems

paper_content:

Trust is an important concept in distributed computing environments and plays a critical role in ensuring and enhancing system security. Although various trust models have been proposed for distributed or pervasive computing systems, little research has been conducted to describe trust in precise and formal way. In this paper, we present a formal definition to express the meaning of trust in distributed computing systems. With this definition, we rigorously analyze the important properties of trust relation, such as reflexivity and conditional transitivity, and describe the trust relations in Role-Based Access Control. Our definition is comprehensive in that the semantic meaning of the trust definition is feasible to describe trust relations in both traditional distributed systems and dynamic pervasive computing environments. This research provides a solid base for formal trust reasoning and effective trust management implementation in distributed systems and pervasive computing environments.
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paper_title: A Distributed Trust Management Mechanism for the Internet of Things Using a Multi-Service Approach

paper_content:

In the Internet of Things (IoT) heterogeneous devices can cooperate and communicate to provide or require determined services. A multi-service IoT is vulnerable to many types of malicious attacks. A trust management scheme is a strategy to establish trust between devices. In this work we propose a distributed trust management model for IoT using direct and indirect observations. The trust of a node is computed by the service quality and recommendations from neighbors. The nodes locally compute the trust of their neighbors, without the need of a central entity. We implemented the proposed strategy in the Cooja simulator of the Contiki operating system to analyze the performance of the trust model. We performed simulations using different number of malicious nodes performing the bad mouthing attack. Simulation results show the trust management scheme is able to detect malicious nodes in the network.
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paper_title: A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion

paper_content:

Abstract Internet of Things (IoT) aims to create a world that enables the interconnection and integration of things in physical world and cyber space. With the involvement of a great number of wireless sensor devices, IoT generates a diversity of datasets that are massive, multi-sourcing, heterogeneous, and sparse. By taking advantage of these data to further improve IoT services and offer intelligent services, data fusion is always employed first to reduce the size and dimension of data, optimize the amount of data traffic and extract useful information from raw data. Although there exist some surveys on IoT data fusion, the literature still lacks comprehensive insight and discussion on it with regard to different IoT application domains by paying special attention to security and privacy. In this paper, we investigate the properties of IoT data, propose a number of IoT data fusion requirements including the ones about security and privacy, classify the IoT applications into several domains and then provide a thorough review on the state-of-the-art of data fusion in main IoT application domains. In particular, we employ the requirements of IoT data fusion as a measure to evaluate and compare the performance of existing data fusion methods. Based on the thorough survey, we summarize open research issues, highlight promising future research directions and specify research challenges.
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paper_title: A System-of-Systems perspective for information fusion system design and evaluation

paper_content:

Abstract This paper provides a System-of-Systems (SoS) perspective for integrated design and evaluation of an Information Fusion System (IFS). IFS is comprised of distributed and heterogeneous systems that accomplish low-level and high-level information fusion (LLIF and HLIF) functionality. LLIF and HLIF functions are developed independent from one another but require collaboration to achieve the IFS mission objectives. The distribution and heterogeneity of systems, in addition to the multiplicity of LLIF and HLIF functions, creates an extensively large design space for the IFS. We apply a SoS engineering architecting process to obtain integrated architectures of IFS and propose guidelines to constrain an otherwise infinite design space of Information Fusion System-of-Systems (IF-SoS). Furthermore, we elaborate a multi-agent system modeling approach and pair it with Design of Experiments for objective evaluation of the IF-SoS design space. The statistical analysis, based on analysis of variance (ANOVA) and Tukey Honest Significant Difference (HSD) Range Tests, quantifies the impact of interactions between LLIF and HLIF design considerations on the IF-SoS performance. Furthermore, statistical evidence is provided to demonstrate that the interactions among JDL levels, in particular between LLIF and HLIF, are the most significant design considerations for fusion performance which necessitate an integrated design and evaluation of LLIF and HLIF—a manifestation of the SoS perspective for the IFS.
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paper_title: A Reliable and Lightweight Trust Computing Mechanism for IoT Edge Devices Based on Multi-Source Feedback Information Fusion

paper_content:

The integration of Internet of Things (IoT) and edge computing is currently a new research hotspot. However, the lack of trust between IoT edge devices has hindered the universal acceptance of IoT edge computing as outsourced computing services. In order to increase the adoption of IoT edge computing applications, first, IoT edge computing architecture should establish efficient trust calculation mechanism to alleviate the concerns of numerous users. In this paper, a reliable and lightweight trust mechanism is originally proposed for IoT edge devices based on multi-source feedback information fusion. First, due to the multi-source feedback mechanism is used for global trust calculation, our trust calculation mechanism is more reliable against bad-mouthing attacks caused by malicious feedback providers. Then, we adopt lightweight trust evaluating mechanism for cooperations of IoT edge devices, which is suitable for large-scale IoT edge computing because it facilitates low-overhead trust computing algorithms. At the same time, we adopt a feedback information fusion algorithm based on objective information entropy theory, which can overcome the limitations of traditional trust schemes, whereby the trust factors are weighted manually or subjectively. And the experimental results show that the proposed trust calculation scheme significantly outperforms existing approaches in both computational efficiency and reliability.
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paper_title: A survey of trust computation models for service management in internet of things systems

paper_content:

Abstract In this paper we survey trust computation models for Internet of things (IoT) systems for the purpose of service management, i.e., whether or not to select an IoT device as a service provider. Future IoT systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects, and are expected to have a high economic impact. To date there is little work on trust computation in IoT environments for service management, especially for dealing with misbehaving owners of IoT devices that provide services to other IoT devices in the system. Our approach is to classify existing trust computation models for service management in IoT systems based on five essential design dimensions for a trust computation model: trust composition, trust propagation, trust aggregation, trust update, and trust formation. We summarize pros and cons of each dimension's options, and highlight the effectiveness of defense mechanisms against malicious attacks. We also summarize the most, least, and little visited trust computation techniques in the literature and provide insight on the effectiveness of trust computation techniques as applying to IoT systems. Finally, we identify gaps in IoT trust computation research and suggest future research directions.
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paper_title: A Mechanism for Securing IoT-enabled Applications at the Fog Layer

paper_content:

The Internet of Things (IoT) is an emerging paradigm branded by heterogeneous technologies composed of smart ubiquitous objects that are seamlessly connected to the Internet. These objects are deployed as Low power and Lossy Networks (LLN) to provide innovative services in various application domains such as smart cities, smart health, and smart communities. The LLN is a form of a network where the interconnected devices are highly resource-constrained (i.e., power, memory, and processing) and characterized by high loss rates, low data rates, and instability in the communication links. Additionally, IoT devices produce a massive amount of confidential and security-sensitive data. Various cryptographic-based techniques exist that can effectively cope with security attacks but are not suitable for IoT as they incur high consumption of resources (i.e., memory, storage and processing). One way to address this problem is by offloading the additional security-related operations to a more resourceful entity such as a fog-based node. Generally, fog computing enables security and analysis of latency-sensitive data directly at the network’s edge. This paper proposes a novel Fog Security Service (FSS) to provide end-to-end security at the fog layer for IoT devices using two well-established cryptographic schemes, identity-based encryption, and identity-based signature. The FSS provides security services such as authentication, confidentiality, and non-repudiation. The proposed architecture would be implemented and evaluated in an OPNET simulator using a single network topology with different traffic loads. The FSS performed better when compared with the APaaS and the legacy method.
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Title: Internet-of-Things and Information Fusion: Trust Perspective Survey

Section 1: Introduction
Description 1: Introduce the importance of IoT and the role of information fusion, identifying trust issues and their impact on IoT environments.

Section 2: Fundamental Trust Model Concepts
Description 2: Outline the basic trust model concepts used to address behavior-related issues in IoT.

Section 3: Behavior Trust
Description 3: Discuss behavior trust as a critical component in Internet-based transactions and its definition in the context of IoT.

Section 4: Reputation
Description 4: Explain the concept of reputation and its role in trust-based decision making within dynamic IoT environments.

Section 5: Honesty
Description 5: Define honesty in the context of IoT trust models and discuss mechanisms to handle dishonest recommenders.

Section 6: Accuracy
Description 6: Define accuracy for information received from recommenders and its importance in trust models.

Section 7: The Need for Trust-Based Information Fusion
Description 7: Discuss the necessity of incorporating trust into information fusion processes to ensure reliable data.

Section 8: Information Fusion, IoT, and Sensors
Description 8: Explain the relationship and processes involved in information fusion, IoT, and their impact on sensor-generated data.

Section 9: Possible Trust Threats Affecting Smart Applications
Description 9: Identify and describe various trust-related threats that can affect the reliability of smart applications.

Section 10: Major Challenges of Trust Models
Description 10: Discuss the significant challenges in designing and implementing trust models for IoT environments.

Section 11: Trust-Based Information Fusion
Description 11: Provide an overview of existing trust-based information fusion methods and their effectiveness.

Section 12: Internet-of-Things Architectures for Modeling Trust
Description 12: Describe different IoT architectures (centralized, distributed, and hybrid) used for modeling trust.

Section 13: Taxonomy of Trust Models
Description 13: Present a detailed taxonomy of trust models highlighting various dimensions used for evaluation.

Section 14: Internet-of-Things Trust Models
Description 14: Classify and discuss existing IoT trust models based on QoS, social attributes, and other factors.

Section 15: Concluding Remarks
Description 15: Summarize the key findings, emphasizing the importance of trust in IoT and information fusion.

Section 16: Information Fusion and Trust
Description 16: Discuss future directions and research areas related to integrating trust into information fusion processes.

Section 17: Fog-Based Distributed Trust Models
Description 17: Explore the potential and challenges of using fog-based distributed trust models in IoT environments.

Section 18: Dynamics of Trust
Description 18: Examine how trust levels should be adjusted over time, including the application of decay functions.

Section 19: Using Trust Decay to Shape the Recommender Set
Description 19: Highlight the importance of shaping the recommender set to maintain trust and avoid misleading recommendations.