Designing End to End Privacy for Open Data Markets in the Internet of Things: A Survey.
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paper_title: Sensing as a Service Model for Smart Cities Supported by Internet of Things

paper_content:

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in ICT to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today infrastructure, platforms, and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the Internet of Things. Our objective is to investigate the concept of sensing as a service model in technological, economical, and social perspectives and identify the major open challenges and issues.
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paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
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paper_title: Context Aware Computing for The Internet of Things: A Survey

paper_content:

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.
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paper_title: Sensing as a Service Model for Smart Cities Supported by Internet of Things

paper_content:

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in ICT to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today infrastructure, platforms, and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the Internet of Things. Our objective is to investigate the concept of sensing as a service model in technological, economical, and social perspectives and identify the major open challenges and issues.
---
paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
---
paper_title: Sensing as a Service Model for Smart Cities Supported by Internet of Things

paper_content:

The world population is growing at a rapid pace. Towns and cities are accommodating half of the world's population thereby creating tremendous pressure on every aspect of urban living. Cities are known to have large concentration of resources and facilities. Such environments attract people from rural areas. However, unprecedented attraction has now become an overwhelming issue for city governance and politics. The enormous pressure towards efficient city management has triggered various Smart City initiatives by both government and private sector businesses to invest in ICT to find sustainable solutions to the growing issues. The Internet of Things (IoT) has also gained significant attention over the past decade. IoT envisions to connect billions of sensors to the Internet and expects to use them for efficient and effective resource management in Smart Cities. Today infrastructure, platforms, and software applications are offered as services using cloud technologies. In this paper, we explore the concept of sensing as a service and how it fits with the Internet of Things. Our objective is to investigate the concept of sensing as a service model in technological, economical, and social perspectives and identify the major open challenges and issues.
---
paper_title: The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

paper_content:

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as Radio frequency identifications, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organizations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. Based on the application domain, we classify and discuss these solutions under five different categories: 1) smart wearable; 2) smart home; 3) smart city; 4) smart environment; and 5) smart enterprise. This survey is intended to serve as a guideline and a conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.
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paper_title: A Taxonomy of Privacy

paper_content:

Privacy is a concept in disarray. Nobody can articulate what it means. As one commentator has observed, privacy suffers from an embarrassment of meanings. Privacy is far too vague a concept to guide adjudication and lawmaking, as abstract incantations of the importance of privacy do not fare well when pitted against more concretely-stated countervailing interests. In 1960, the famous torts scholar William Prosser attempted to make sense of the landscape of privacy law by identifying four different interests. But Prosser focused only on tort law, and the law of information privacy is significantly more vast and complex, extending to Fourth Amendment law, the constitutional right to information privacy, evidentiary privileges, dozens of federal privacy statutes, and hundreds of state statutes. Moreover, Prosser wrote over 40 years ago, and new technologies have given rise to a panoply of new privacy harms. A new taxonomy to understand privacy violations is thus sorely needed. This article develops a taxonomy to identify privacy problems in a comprehensive and concrete manner. It endeavors to guide the law toward a more coherent understanding of privacy and to serve as a framework for the future development of the field of privacy law.
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paper_title: Privacy and Data Protection by Design - from policy to engineering

paper_content:

Privacy and data protection constitute core values of individuals and of democratic societies. There have been decades of debate on how those values -and legal obligations- can be embedded into systems, preferably from the very beginning of the design process. One important element in this endeavour are technical mechanisms, known as privacy-enhancing technologies (PETs). Their effectiveness has been demonstrated by researchers and in pilot implementations. However, apart from a few exceptions, e.g., encryption became widely used, PETs have not become a standard and widely used component in system design. Furthermore, for unfolding their full benefit for privacy and data protection, PETs need to be rooted in a data governance strategy to be applied in practice. This report contributes to bridging the gap between the legal framework and the available technological implementation measures by providing an inventory of existing approaches, privacy design strategies, and technical building blocks of various degrees of maturity from research and development. Starting from the privacy principles of the legislation, important elements are presented as a first step towards a design process for privacy-friendly systems and services. The report sketches a method to map legal obligations to design strategies, which allow the system designer to select appropriate techniques for implementing the identified privacy requirements. Furthermore, the report reflects limitations of the approach. It concludes with recommendations on how to overcome and mitigate these limits.
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paper_title: Fog computing and its role in the internet of things

paper_content:

Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Wide-spread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Heterogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid, Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).
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paper_title: The Dataware manifesto

paper_content:

In this paper we concern ourselves with Service-Oriented Architectures (SOA) in the “business to consumer” (B2C) arena. In particular we consider the services required to enable consumers to combine data they possess with data held about them by businesses and government. We introduce the concept of Dataware as the logical federation of data sources containing “my data” and discuss an SOA to deliver new and compelling services and applications able to reap the benefits of value-in-use for consumers.
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paper_title: Privacy Design Strategies

paper_content:

In this paper we define the notion of a privacy design strategy. These strategies help IT architects to support privacy by design early in the software development life cycle, during concept development and analysis. Using current data protection legislation as point of departure we derive the following eight privacy design strategies: minimise, hide, separate, aggregate, inform, control, enforce, and demonstrate. The strategies also provide a useful classification of privacy design patterns and the underlying privacy enhancing technologies. We therefore believe that these privacy design strategies are not only useful when designing privacy friendly systems, but also helpful when evaluating the privacy impact of existing IT systems.
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paper_title: Engineering Privacy by Design

paper_content:

The design and implementation of privacy requirements in systems is a difficult problem and requires the translation of complex social, legal and ethical concerns into systems requirements. The concept of “privacy by design” has been proposed to serve as a guideline on how to address these concerns. “Privacy by design” consists of a number of principles that can be applied from the onset of systems development to mitigate privacy concerns and achieve data protection compliance. However, these principles remain vague and leave many open questions about their application when engineering systems. In this paper we show how starting from data minimization is a necessary and foundational first step to engineer systems in line with the principles of privacy by design. We first discuss what data minimization can mean from a security engineering perspective. We then present a summary of two case studies in which privacy is achieved by minimizing different types of data, according to the purpose of each application. First, we present a privacypreserving ePetition system, in which user’s privacy is guaranteed by hiding their identity from the provider while revealing their votes. Secondly, we study a road tolling system, in which users have to be identified for billing reasons and data minimization is applied to protect further sensitive information (in this case location information). The case studies make evident that the application of data minimization does not necessarily imply anonymity, but may also be achieved by means of concealing information related to identifiable individuals. In fact, different kinds of data minimization are possible, and each system requires careful crafting of data minimization best suited for its purpose. Most importantly, the two case studies underline that the interpretation of privacy by design principles requires specific engineering expertise, contextual analysis, and a balancing of multilateral security and privacy interests. They show that privacy by design is a productive space in which there is no one way of solving the problems. Based on our analysis of the two case studies, we argue that engineering systems according to the privacy by design principles requires the development of generalizable methodologies that build upon the principle of data minimization. However, the complexity of this engineering task demands caution against reducing such methodologies to “privacy by design check lists” that can easily be ticked away for compliance reasons while not mitigating some of the risks that privacy by design is meant to address.
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paper_title: k-Anonymity: A Model for Protecting Privacy

paper_content:

Consider a data holder, such as a hospital or a bank, that has a privately held collection of person-specific, field structured data. Suppose the data holder wants to share a version of the data with researchers. How can a data holder release a version of its private data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful? The solution provided in this paper includes a formal protection model named k-anonymity and a set of accompanying policies for deployment. A release provides k-anonymity protection if the information for each person contained in the release cannot be distinguished from at least k-1 individuals whose information also appears in the release. This paper also examines re-identification attacks that can be realized on releases that adhere to k- anonymity unless accompanying policies are respected. The k-anonymity protection model is important because it forms the basis on which the real-world systems known as Datafly, µ-Argus and k-Similar provide guarantees of privacy protection.
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paper_title: The Algorithmic Foundations of Differential Privacy

paper_content:

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition.After motivating and discussing the meaning of differential privacy, the preponderance of this monograph is devoted to fundamental techniques for achieving differential privacy, and application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some astonishingly powerful computational results, there are still fundamental limitations — not just on what can be achieved with differential privacy but on what can be achieved with any method that protects against a complete breakdown in privacy. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power. Certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed.We then turn from fundamentals to applications other than queryrelease, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams is discussed.Finally, we note that this work is meant as a thorough introduction to the problems and techniques of differential privacy, but is not intended to be an exhaustive survey — there is by now a vast amount of work in differential privacy, and we can cover only a small portion of it.
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paper_title: User Perception of Facebook App Data Access: A Comparison of Methods and Privacy Concerns

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Users share vast amounts of personal information online, but are they fully aware of what information they are sharing and with whom? In this paper, we focused on Facebook apps and set out to understand how concerned users are about privacy and how well-informed they are about what personal data apps can access. We found that initially, subjects were generally under-informed about what data apps could access from their profiles. After viewing additional information about these permissions, subjects’ concern about privacy on Facebook increased. Subjects’ understanding of what data apps were able to access increased, although even after receiving explicit information on the topic, many subjects still did not fully understand the extent to which apps could access their data.
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paper_title: Privacy risk models for designing privacy-sensitive ubiquitous computing systems

paper_content:

Privacy is a difficult design issue that is becoming increasingly important as we push into ubiquitous computing environments. While there is a fair amount of theoretical work on designing for privacy, there are few practical methods for helping designers create applications that provide end-users with a reasonable level of privacy protection that is commensurate with the domain, with the community of users, and with the risks and benefits to all stakeholders in the intended system. Towards this end, we propose privacy risk models as a general method for refining privacy from an abstract concept into concrete issues for specific applications and prioritizing those issues. In this paper, we introduce a privacy risk model we have developed specifically for ubiquitous computing, and outline two case studies describing our use of this privacy risk model in the design of two ubiquitous computing applications.
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Title: Designing End to End Privacy for Open Data Markets in the Internet of Things: A Survey

Section 1: Introduction
Description 1: Introduce the concepts of IoT, sensing as a service, and the significance of data sharing in open data markets, while highlighting the privacy risks involved.

Section 2: Vision towards Liberating Data
Description 2: Introduce the sensing as a service model, describe data exchange between data owners and consumers, and outline the creation of open data markets.

Section 3: Motivation for End to End Privacy Protection
Description 3: Discuss the privacy challenges in IoT through practical use cases, illustrating how data flows and the associated privacy risks.

Section 4: Technologies for Privacy Preservation
Description 4: Discuss existing privacy-preserving strategies and design techniques to ensure stakeholder privacy during data trading.

Section 5: Definition of Privacy
Description 5: Discuss the concept of privacy and its dimensions, including legal perspectives and privacy protection goals.

Section 6: Phases in Data Life Cycle
Description 6: Describe the different phases of the data life cycle in IoT and the balancing act between edge and cloud computing regarding privacy.

Section 7: Privacy Preserving Strategies and Design Techniques
Description 7: Introduce and discuss various privacy-preserving strategies and techniques from an IoT perspective, detailing their application during different data life cycle phases.

Section 8: Research Challenges and Future Direction
Description 8: Highlight major research challenges in privacy-preserving data analysis in the IoT domain and suggest future directions for realizing open data markets.

Section 9: Conclusions
Description 9: Summarize the importance of privacy protection in open data markets, reiterate the benefits of the sensing as a service model, and emphasize the need for future research to address identified challenges.