EnhanEigen: A New Comprehensive Trust Model for Peer-to-Peer Network

Abstract

In this paper, we propose a new trust model called EnhanEigen. This model uses the comprehensive trust to evaluate the peers and enhanced probabilistic peer selection algorithm to filter malicious peers and select the peers with high trust value. This comprehensive trust is composed of local trust value, global trust value, malicious percent (MP) and feedback consistency percent (FCP). MP and FCP are important parameters to help filter malicious peers. In experiments, good peers, malicious and malign peers, feedback cheating peers are used to validate the performance of the new trust model in peer to peer file sharing environment. Experiment show that the new trust model can greatly reduce the false feedbacks adopted by the network, has the shorter algorithm execution time and has a higher success rate of transactions. The new model can distinguish false feedbacks to resist the cooperative attacks from malicious peers and feedback cheating peers effectively.