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Effective Usage of Computational Trust Models in Rational Environments

Published:01 October 2011Publication History
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Abstract

Computational reputation-based trust models using statistical learning have been intensively studied for distributed systems where peers behave maliciously. However practical applications of such models in environments with both malicious and rational behaviors are still very little understood. In this article, we study the relation between their accuracy measures and their ability to enforce cooperation among participants and discourage selfish behaviors. We provide theoretical results that show the conditions under which cooperation emerges when using computational trust models with a given accuracy, and how cooperation can still be sustained while reducing the cost and accuracy of those models.

Specifically, we propose a peer selection protocol that uses a computational trust model as a dishonesty detector to filter out unfair ratings. We prove that such a model with reasonable misclassification error bound in identifying malicious ratings can effectively build trust and cooperation in the system, considering rationality of participants. These results reveal two interesting observations. First, the key to the success of a reputation system in a rational environment is not a sophisticated trust-learning mechanism, but an effective identity-management scheme to prevent whitewashing behaviors. Second, given an appropriate identity-management mechanism, a reputation-based trust model with a moderate accuracy bound can be used to effectively enforce cooperation in systems with both rational and malicious participants. As a result, in heterogeneous environments where peers use different algorithms to detect misbehavior of potential partners, cooperation may still emerge. We verify and extend these theoretical results to a variety of settings involving honest, malicious, and strategic players through extensive simulation. These results will enable a much more targeted, cost-effective and realistic design for decentralized trust management systems, such as needed for peer-to-peer, electronic commerce, or community systems.

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          • Published in

            cover image ACM Transactions on Autonomous and Adaptive Systems
            ACM Transactions on Autonomous and Adaptive Systems  Volume 6, Issue 4
            October 2011
            171 pages
            ISSN:1556-4665
            EISSN:1556-4703
            DOI:10.1145/2019591
            Issue’s Table of Contents

            Copyright © 2011 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 1 October 2011
            • Accepted: 1 August 2010
            • Revised: 1 September 2009
            • Received: 1 August 2008
            Published in taas Volume 6, Issue 4

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