A new reputation mechanism against dishonest recommendations in P2P systems

In peer-to-peer (P2P) systems, peers often must interact with unknown or unfamiliar peers without the benefit of trusted third parties or authorities to mediate the interactions. Trust management through reputation mechanism to facilitate such interactions is recognized as an important element of P2P systems. However current P2P reputation mechanism can not process such strategic recommendations as correlative and collusive ratings. Furthermore in them there exists unfairness to blameless peers. This paper presents a new reputation mechanism for P2P systems. It has a unique feature: a recommender's credibility and level of confidence about the recommendation is considered in order to achieve a more accurate calculation of reputations and fair evaluation of recommendations. Theoretic analysis and simulation show that the reputation mechanism we proposed can help peers effectively detect dishonest recommendations in a variety of scenarios where more complex malicious strategies are introduced.