ICIS '00 Proceedings of the twenty first international conference on Information systems
Consumer trust in an Internet store
Information Technology and Management
A Social Mechanism of Reputation Management in Electronic Communities
CIA '00 Proceedings of the 4th International Workshop on Cooperative Information Agents IV, The Future of Information Agents in Cyberspace
A Computational Model of Trust and Reputation for E-businesses
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
Detecting deception in reputation management
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Robust incentive techniques for peer-to-peer networks
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Review on Computational Trust and Reputation Models
Artificial Intelligence Review
The Knowledge Engineering Review
Coping with inaccurate reputation sources: experimental analysis of a probabilistic trust model
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
An integrated trust and reputation model for open multi-agent systems
Autonomous Agents and Multi-Agent Systems
Witness-Based Collusion and Trust-Aware Societies
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Towards con-resistant trust models for distributed agent systems
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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In ways analogous to humans, autonomous agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably. This paper defines a class of attacks called witness-based collusion attacks designed to exploit trust and reputation models. Empirical results demonstrate that unidimensional trust models are vulnerable to witness-based collusion attacks in ways independent multidimensional trust models are not. This paper analyzes the impact of the proportion of witness-based colluding agents on the society. Furthermore, it demonstrates that here is a need for witness interaction trust to detect colluding agents in addition to the need for direct interaction trust to detect malicious agents. By proposing a set of policies, the paper demonstrates how learning agents can decrease the level of encounter risk in a witness-based collusive society.