An Adaptive Group-Based Reputation System in Peer-to-Peer Networks

As more and more P2P applications being popular in Internet, one of important problem to be solved is inspiring users to cooperate each other actively and honestly, the reputation mechanism which is a hot spot for P2P research has been proposed to conquer it. Because of the characters of virtuality and anonymous in the network, it is very easy for users with bad reputations to reenter the system with new identities to regain new reputations in the reputation systems. In order to get rid of the impact of whitewashers and improve the system performance and efficiency, we propose a new probability-based adaptive initial reputation mechanism. In this new mechanism, newcomers will be trusted based on system’s trust-probability which can be adjusted according to the actions of the newcomers. To avoid the system fluctuating for actions of a few whitewashers, we realize the new reputation mechanism in system with group-based architecture, which can localize the impact of whitewashers in their own groups. Both performance analysis and simulation show that this new adaptive reputation mechanism is more effective.