AbsoluteTrust: Algorithm for Aggregation of Trust in Peer-to-Peer Networks

To mitigate the attacks by malicious peers and to isolate them in peer-to-peer (P2P) networks, several reputation systems have been proposed in the past. The relative ranking method is the most popular among them. In this method, peers are ranked according to their reputation in the network. The major limitation of this method is that it does not give any absolute interpretation about the peers, it can only differentiate among the given set of peers. This is more significant when all the peers responding to a query, are malicious. In such a situation, we can only know that who is better among them without knowing their actual reputation in the whole network. In this article, we are proposing a new algorithm which can rank the peers in the whole network as well as can give an absolute interpretation of their reputation. Consequently, we can identify them as good peers or malicious peers. Further, by choosing the suitable values of parameters, our algorithm converges much faster at some global consensus. Simulation results show that it performs better in load balancing and in reducing the inauthentic downloads in the network as compared to the existing algorithms.