Detecting malicious peers in a reputation-based peer-to-peer system

In this paper we propose a reputation management scheme for partially decentralized peer-to-peer systems. The reputation scheme helps building trust between peers based on their past experiences and feedbacks from other peers. Our system is novel in that it is able to detect not only malicious peers sending inauthentic files but also malicious peers that are lying in their feedbacks. To detect those peers, we introduce the new concept of suspicious transactions. The simulation results show that the proposed scheme is able to effectively detect malicious peers and isolate them from the system, hence reducing the amount of inauthentic uploads and increasing peers´ satisfaction.