Managing trust in a peer-2-peer information system
Proceedings of the tenth international conference on Information and knowledge management
Choosing reputable servents in a P2P network
Proceedings of the 11th international conference on World Wide Web
An evidential model of distributed reputation management
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
A reputation-based approach for choosing reliable resources in peer-to-peer networks
Proceedings of the 9th ACM conference on Computer and communications security
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Limited reputation sharing in P2P systems
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Reputation Management Framework and Its Use as Currency in Large-Scale Peer-to-Peer Networks
P2P '04 Proceedings of the Fourth International Conference on Peer-to-Peer Computing
An incentives' mechanism promoting truthful feedback in peer-to-peer systems
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
Bayesian network trust model in peer-to-peer networks
AP2PC'03 Proceedings of the Second international conference on Agents and Peer-to-Peer Computing
APNOMS '08 Proceedings of the 11th Asia-Pacific Symposium on Network Operations and Management: Challenges for Next Generation Network Operations and Service Management
@Trust: A trust model based on feedback-arbitration in structured P2P network
Computer Communications
An integrated approach for trust management based on policy, community adherence and reputation
International Journal of Ad Hoc and Ubiquitous Computing
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The main challenge in reputation system is to identify false feedbacks. However current reputation models in peer-to-peer systems can not process such strategic feedbacks as correlative and collusive ratings. Furthermore in them there exists unfairness to blameless peers. We propose a new reputation-based trust management mechanism to process false feedbacks. Our method uses two metrics to evaluate peers: feedback and service trust. Service trust shows the reliability of providing service. Feedback trust can reflect credibility of reporting ratings. Service trust of sever and feedback trust of consumer are separately updated after a transaction, furthermore the former is closely related to the latter. Besides reputation model we also propose a punishment mechanism to prevent malicious servers and liars from iteratively exerting bad behaviors in the system. Simulation shows our approach can effectively process aforesaid strategic feedbacks and mitigate unfairness.