A Trust-Based Reputation Management System
TCD-CS-2007-44.pdf (thesis or dissertation) 1.837Mb
This thesis describes a trust-based reputation management system (RMS) that addresses each of the above issues. The system resolves the ease-of-use versus accuracy problem by maintaining usability viii but with enhanced collection and analysis of evidence with regard to domain-specific behaviour. Furthermore, the system provides increased accuracy of evidentiary analysis with regard to context by assessing evidence in terms of role, timeliness, and environment. Interaction dynamics are also considered in the system?s decision-making process, thus providing for the ability to limit exposure to risk from unreliable recommendations as well as the ability to assess the likelihood of colluding behaviour. The risk of an interaction resulting in malicious behaviour is explicitly analysed and stated to the user. Finally, the reputation summary is replaced by the explicit assessment of the trust and risk involved in interacting with another user, providing a security decision as advice to a user on whether or not to engage in an interaction. The RMS builds on the work of the SECURE (Secure Environments for Collaboration among Ubiquitous Roaming Entities) project. Grounded on a formal model, the SECURE trust-based decision-making framework applies trust and risk to evidence in a manner comparable to the human decision-making process. We use the SECURE model as a basis with which to design our own application-specific mechanisms for reputation management in Internet auctions, and these mechanisms provide for the observation of domain-specific behaviour such as fraud and theft, assessment of contextual relevance, and analysis of risk in financial terms that is made explicit to the end user. Additionally, in the reputation management for Internet auctions application domain, SECURE is deficient in analysing the dynamic aspects of marketplace networks, and therefore we design additional techniques for interaction management. These techniques underlie an extension to the SECURE framework that includes methods for the weighting of recommendations based on the application of recommendation weighting policy to trustworthy recommendation paths within the graph of marketplace participants; and the identification of colluding behaviour between users within the marketplace community, by assessing interaction dynamics between users over time. Our evaluation of the RMS shows that it reduces complexity, increases accuracy, and maintains usability of reputation management for Internet auction users. It validates that the RMS, in its observation and identification of normal and abnormal domain-specific behaviour, reduces complexity by providing accurate decision-making advice to users. Furthermore, the evaluation confirms that the analysis of context in terms of role, time, and environmental factors can further reduce complexity in the decision-making process while maintaining usability. Additionally, the evaluation demonstrates that recommendation weighting can protect a user against the potential unreliability of recommended evidence. Finally, the evaluation establishes that a reputation management system based on a computational trust-based decision-making model can counter the issues in existing commercial reputation management systems and provide increased benefit to users interacting in the Internet auction domain.
Author: Gray, Elizabeth
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