Managing trust in a peer-2-peer information system
Proceedings of the tenth international conference on Information and knowledge management
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Communications of the ACM - Supporting community and building social capital
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
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HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
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ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
Exchange-Based Incentive Mechanisms for Peer-to-Peer File Sharing
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
Non-Cooperation in Competitive P2P Networks
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
BambooTrust: practical scalable trust management for global public computing
Proceedings of the 2006 ACM symposium on Applied computing
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iTrust'03 Proceedings of the 1st international conference on Trust management
Iterative Filtering in Reputation Systems
SIAM Journal on Matrix Analysis and Applications
Using jiminy for run-time user classification based on rating behaviour
iTrust'06 Proceedings of the 4th international conference on Trust Management
Credible recommendation exchange mechanism for P2P reputation systems
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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In this paper we present the design, implementation, and evaluation of Jiminy: a framework for explicitly rewarding users who participate in reputation management systems by submitting ratings. To defend against participants who submit random or malicious ratings in order to accumulate rewards, Jiminy facilitates a probabilistic mechanism to detect dishonesty and halt rewards accordingly. Jiminy's reward model and honesty detection algorithm are presented and its cluster-based implementation is described. The proposed framework is evaluated using a large sample of real-world user ratings in order to demonstrate its effectiveness. Jiminy's performance and scalability are analysed through experimental evaluation. The system is shown to scale linearly with the on-demand addition of slave machines to the Jiminy cluster, allowing it to successfully process large problem spaces.