Peer-to-peer's most wanted: Malicious peers

In this paper, we propose a reputation management scheme for partially decentralized peer-to-peer systems. The reputation scheme helps to build trust among peers based on their past experiences and feedback from other peers. Two selection advisor algorithms are proposed for helping peers to select the most trustworthy peer to download from. The proposed algorithms can detect malicious peers sending inauthentic files. The Malicious Detector Algorithm is also proposed to detect liar peers that send the wrong feedback to subvert the reputation system. The new concept of Suspicious Transactions is introduced and explained. Simulation results confirm the capability of the proposed algorithms to effectively detect malicious peers and isolate them from the system, hence reducing the amount of inauthentic uploads, increasing peers’ satisfaction, and preserving network resources.