STTM: Similarity Transitivity Chain Based Trust Model in P2P Environment

Trust mechanism is a crucial part of the P2P applications, which limits their rapid development. Unfortunately, current mechanisms were unable to detect the malicious peers accurately under the disturbing of various malicious reports. This paper proposes a new trust model, named Similarity Transitivity chain based Trust Model (STTM), to evaluate peers´ global trust more precisely. Firstly, we employ PeerStrategy to produce feedbacks. Then we offer a novel similarity transitivity chain, which is formed by the peers who have common neighbors, to calculate report trustworthiness. By considering the peer´s feedbacks as a vector, we calculate the personal similarity of each pair that has common neighbors. After that, we transit such personal similarities through the chain and get the report trustworthiness vector when all the peers come to a static view. Finally, we make use of maximum likelihood estimation equation to compute global trust. The simulation results show that our trust model is able to estimate peers´ global trust accurately in most scenarios, especially in the scenario of two collusion groups. Also, it sharply decreases the mean error of trust estimation and performs better than other trust models.