Reputation Management Survey
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paper_title: From trading to eCommunity population: Responding to social and contractual challenges

paper_content:

The emergence of networked eBusiness and the wave of service-oriented computing facilities create new challenges for automating inter-enterprise business process management and eContracting. This development leads to strategical benefits for agile enterprises, but also to new challenges on enterprise system architectures and platforms. This paper discusses the techniques of introducing trust-related decisions into eContracting, and their effects. This work enhances the web-Pilarcos project results on B2B interoperability middleware; the architectural model supported comprises of autonomous business services forming loosely-coupled, eContract-governed eCommunities
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paper_title: Operational Models for Reputation Servers

paper_content:

This paper devises a classification system for reputation systems based on two axes, namely: who performs the evaluation of a subject's reputation, and how the information is collected by the reputation system. This leads to 4 possible operational models for reputation systems, termed the Voting Model, the Opinion Poll Model, the MP Model and the Research Model, each of which is then analyzed. Finally, the paper postulates the inherent trustworthiness of each operational model, and concludes with a hypothesis of how these systems might evolve in the future.
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paper_title: Managing trust in a peer-2-peer information system

paper_content:

Managing trust is a problem of particular importance in peer-to-peer environments where one frequently encounters unknown agents. Existing methods for trust management, that are based on reputation, focus on the semantic properties of the trust model. They do not scale as they either rely on a central database or require to maintain global knowledge at each agent to provide data on earlier interactions. In this paper we present an approach that addresses the problem of reputation-based trust management at both the data management and the semantic level. We employ at both levels scalable data structures and algorithms that require no central control and allow to assess trust by computing an agents reputation from its former interactions with other agents. Thus the meethod can be implemented in a peer-to-peer environment and scales well for very large numbers of participants. We expect that scalable methods for trust management are an important factor, if fully decentralized peer-to-peer systems should become the platform for more serious applications than simple file exchange.
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paper_title: A probabilistic trust model for handling inaccurate reputation sources

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This research aims to develop a model of trust and reputation that will ensure good interactions amongst software agents in large scale open systems in particular. The following are key drivers for our model: (1) agents may be self-interested and may provide false accounts of experiences with other agents if it is beneficial for them to do so; (2) agents will need to interact with other agents with which they have no past experience. 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. 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: Architecture and Algorithms for a Distributed Reputation System

paper_content:

Trust is an essential component of successful interactions in social life as well as in business relationships. In this paper we propose a system that closely reflects real-world trust building in an online environment. We describe the models used to represent trust in entities in various categories, algorithms to calculate and update trust based on experiences of entities with each other and the agent interactions necessary for finding and exchanging trust information.
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paper_title: Cooperative Peer Groups in NICE

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We present a distributed scheme for trust inference in peer-to-peer networks. Our work is in the context of the NICE system, which is a platform for implementing cooperative applications over the Internet. We describe a technique for efficiently storing user reputation information in a completely decentralized manner, and show how this information can be used to efficiently identify non-cooperative users in NICE. We present a simulation-based study of our algorithms, in which we show our scheme scales to thousands of users using modest amounts of storage, processing, and bandwidth at any individual node. Lastly we show that our scheme is robust and can form cooperative groups in systems where the vast majority of users are malicious.
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paper_title: Trusted P2P transactions with fuzzy reputation aggregation

paper_content:

Internet commerce and online commodity exchanges suffer from distrust among sellers and buyers, who are often strangers to each other. The authors present a new P2P reputation system based on fuzzy logic inferences, which can better handle uncertainty, fuzziness, and incomplete information in peer trust reports. This system aggregates peer reputations with affordable message overhead. By testing the system using eBay transaction data in the public domain, the authors seek to demonstrate the efficacy and robustness of two P2P reputation systems - fuzzytrust and eigentrust - at establishing trust among the peers in P2P applications.
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paper_title: PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities

paper_content:

Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.
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paper_title: Maximum Likelihood Estimation of Peers" Performance in P2P Networks

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The problem of encouraging trustworthy behavior in P2P online communities by managing peers’ reputations has drawn a lot of attention recently. However, most of the proposed solutions exhibit the following two problems: huge implementation overhead and unclear trust related model semantics. In this paper we show that a simple probabilistic technique, maximum likelihood estimation namely, can reduce these two problems substantially when employed as the feedback aggregation strategy. Thus, no complex exploration of the feedback is necessary. Instead, simple, intuitive and efficient probabilistic estimation methods suffice.
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paper_title: Reputation and social network analysis in multi-agent systems

paper_content:

The use of previous direct interactions is probably the best way to calculate a reputation but, unfortunately this information is not always available. This is especially true in large multi-agent systems where interaction is scarce. In this paper we present a reputation system that takes advantage, among other things, of social relations between agents to overcome this problem.
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paper_title: The Eigentrust algorithm for reputation management in P2P networks

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Peer-to-peer file-sharing networks are currently receiving much attention as a means of sharing and distributing information. However, as recent experience shows, the anonymous, open nature of these networks offers an almost ideal environment for the spread of self-replicating inauthentic files.We describe an algorithm to decrease the number of downloads of inauthentic files in a peer-to-peer file-sharing network that assigns each peer a unique global trust value, based on the peer's history of uploads. We present a distributed and secure method to compute global trust values, based on Power iteration. By having peers use these global trust values to choose the peers from whom they download, the network effectively identifies malicious peers and isolates them from the network.In simulations, this reputation system, called EigenTrust, has been shown to significantly decrease the number of inauthentic files on the network, even under a variety of conditions where malicious peers cooperate in an attempt to deliberately subvert the system.
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paper_title: Mapping the Gnutella Network: Properties of Large-Scale Peer-to-Peer Systems and Implications for System Design

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Despite recent excitement generated by the peer-to-peer (P2P) paradigm and the surprisingly rapid deployment of some P2P applications, there are few quantitative evaluations of P2P systems behavior. The open architecture, achieved scale, and self-organizing structure of the Gnutella network make it an interesting P2P architecture to study. Like most other P2P applications, Gnutella builds, at the application level, a virtual network with its own routing mechanisms. The topology of this virtual network and the routing mechanisms used have a significant influence on application properties such as performance, reliability, and scalability. We have built a "crawler" to extract the topology of Gnutella's application level network. In this paper we analyze the topology graph and evaluate generated network traffic. Our two major findings are that: (1) although Gnutella is not a pure power-law network, its current configuration has the benefits and drawbacks of a power-law structure, and (2) the Gnutella virtual network topology does not match well the underlying Internet topology, hence leading to ineffective use of the physical networking infrastructure. These findings guide us to propose changes to the Gnutella protocol and implementations that may bring significant performance and scalability improvements. We believe that our findings as well as our measurement and analysis techniques have broad applicability to P2P systems and provide unique insights into P2P system design tradeoffs.
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paper_title: Reputation and social network analysis in multi-agent systems

paper_content:

The use of previous direct interactions is probably the best way to calculate a reputation but, unfortunately this information is not always available. This is especially true in large multi-agent systems where interaction is scarce. In this paper we present a reputation system that takes advantage, among other things, of social relations between agents to overcome this problem.
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Title: Reputation Management Survey

Section 1: Introduction
Description 1: Provide a background on the importance of reputation systems in online collaborations and outline the primary objectives of the paper.

Section 2: Taxonomy of credibility aspects
Description 2: Describe the taxonomy that covers creation and content of recommendations, selection and use of recommenders, and interpretation and reasoning applied to gathered information.

Section 3: Compared reputation systems
Description 3: Present an overview and comparison of eleven chosen reputation systems based on their credibility analysis methods.

Section 4: Recommendation creation and content
Description 4: Compare different approaches to creating a recommendation, detailing how experience information is conveyed and what metadata is included.

Section 5: Selection and use of recommenders
Description 5: Analyze the criteria for selecting recommenders, methods for gathering information, and the impact on the quality of reputation estimates.

Section 6: Reasoning and interpretation
Description 6: Discuss the methods for aggregating reputation information, interpreting the final estimate, and evaluating its credibility or reliability.

Section 7: Conclusions
Description 7: Summarize the findings from the survey, focusing on social requirements, scalability, and recommendations for the future development of reputation systems.