Trust networks consist of transitive trust relationships between people, organisations and software agents connected through a medium for communication and interaction. By formalising trust relationships, e.g. as reputation scores or as subjective trust measures, trust between parties within the community can be derived by analysing the trust paths linking the parties together. This article describes a method for trust network analysis using subjective logic (TNA-SL). It provides a simple notation for expressing transitive trust relationships, and defines a method for simplifying complex trust networks so that they can be expressed in a concise form and be computationally analysed. Trust measures are expressed as beliefs, and subjective logic is used to compute trust between arbitrary parties in the network. We show that TNA-SL is efficient, and illustrate possible applications with examples.

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Trust network analysis with subjective logic

SUMMARY The range of applications of wireless sensor networks is so wide that it tends to invade our every day life. In the future, a sensor network will survey our health, our home, the roads we follow, the office or the industry we work in or even the aircrafts we use, in an attempt to enhance our safety. However, the wireless sensor networks themselves are prone to security attacks. The list of security attacks, although already very long, continues to augment impeding the expansion of these networks. The trust management schemes consist of a powerful tool for the detection of unexpected node behaviours (either faulty or malicious). Once misbehaving nodes are detected, their neighbours can use this information to avoid cooperating with them, either for data forwarding, data aggregation or any other cooperative function. A variety of trust models which follow different directions regarding the distribution of measurement functionality, the monitored behaviours and the way measurements are used to calculate/define the node’s trustworthiness has been presented in the literature. In this paper, we survey trust models in an attempt to explore the interplay among the implementation requirements, the resource consumption and the achieved security. Our goal is to draw guidelines for the design of deployable trust model designs with respect to the available node and network capabilities and application peculiarities. Copyright © 2010 John Wiley & Sons, Ltd.

Trust management in wireless sensor networks

Online Social Networks (OSNs) are becoming a popular method of meeting people and keeping in touch with friends. OSNs resort to trust evaluation models and algorithms to improve service quality and enhance user experiences. Much research has been done to evaluate trust and predict the trustworthiness of a target, usually from the view of a source. Graph-based approaches make up a major portion of the existing works, in which the trust value is calculated through a trusted graph (or trusted network, web of trust, or multiple trust chains). In this article, we focus on graph-based trust evaluation models in OSNs, particularly in the computer science literature. We first summarize the features of OSNs and the properties of trust. Then we comparatively review two categories of graph-simplification-based and graph-analogy-based approaches and discuss their individual problems and challenges. We also analyze the common challenges of all graph-based models. To provide an integrated view of trust evaluation, we conduct a brief review of its pre- and postprocesses (i.e., the preparation and validation of trust models, including information collection, performance evaluation, and related applications). Finally, we identify some open challenges that all trust models are facing.

https://dl.acm.org/doi/pdf/10.1145/2906151

Understanding Graph-Based Trust Evaluation in Online Social Networks: Methodologies and Challenges

The concept of trust and/or trust management has received considerable attention in engineering research communities as trust is perceived as the basis for decision making in many contexts and the motivation for maintaining long-term relationships based on cooperation and collaboration Even if substantial research effort has been dedicated to addressing trust-based mechanisms or trust metrics (or computation) in diverse contexts, prior work has not clearly solved the issue of how to model and quantify trust with sufficient detail and context-based adequateness The issue of trust quantification has become more complicated as we have the need to derive trust from complex, composite networks that may involve four distinct layers of communication protocols, information exchange, social interactions, and cognitive motivations In addition, the diverse application domains require different aspects of trust for decision making such as emotional, logical, and relational trust This survey aims to outline the foundations of trust models for applications in these contexts in terms of the concept of trust, trust assessment, trust constructs, trust scales, trust properties, trust formulation, and applications of trust We discuss how different components of trust can be mapped to different layers of a complex, composite network; applicability of trust metrics and models; research challenges; and future work directions

https://dl.acm.org/doi/pdf/10.1145/2815595

A Survey on Trust Modeling

In online social networks (OSNs), to evaluate trust from one user to another indirectly connected user, the trust evidence in the trusted paths (i.e., paths built through intermediate trustful users) should be carefully treated. Some paths may overlap with each other, leading to a unique challenge of path dependence , i.e., how to aggregate the trust values of multiple dependent trusted paths. OSNs bear the characteristic of high clustering, which makes the path dependence phenomenon common. Another challenge is trust decay through propagation, i.e., how to propagate trust along a trusted path, considering the possible decay in each node. We analyze the similarity between trust propagation and network flow, and convert a trust evaluation task with path dependence and trust decay into a generalized network flow problem. We propose a modified flow-based trust evaluation scheme GFTrust , in which we address path dependence using network flow, and model trust decay with the leakage associated with each node. Experimental results, with the real social network data sets of Epinions and Advogato, demonstrate that GFTrust can predict trust in OSNs with a high accuracy, and verify its preferable properties.

Trust Evaluation in Online Social Networks Using Generalized Network Flow

Economic and social activity is increasingly reflected in operations on digital objects and network-mediated interactions between digital entities. Trust is a prerequisite for many of these interactions, particularly if items of value are to be exchanged. In this paper the probabilistic model and computational approaches found in some network reliability models are applied to modelling computational trust. The result is a new generalized trust model called the Generic Reliability Trust Model or GRTM and a new transitive trust metric called Hop-Count Limited Transitive Trust (HLTT). A conservative approximation heuristic is defined which leads to more practical algorithm performance. Results from a JAVA-based implementation, utilizing an XMLbased trust-graph representation and a random power-law trust graph generator, demonstrate potential for application to large ad-hoc trust networks.

Glenn Mahoney

Papers

Generic Reliability Trust Model.