A New Reputation-Based Trust Management Mechanism Against False Feedbacks in Peer-to-Peer Systems
Abstract: 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.
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