Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to

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.

The openness and anonymity of P2P file-sharing networks have been widely accepted over the last few years. Enormous file-sharing communities in which numerous anonymous users share a variety of resources have been established with the aid of the P2P networks. Users can join the communities with ease without disclosing their identities. However, the openness and anonymity raises the problem of trust, because openness and anonymity also assist malicious users in exploiting the networks and, at the same time, complicate their detection and location. We propose a remedy for this trust problem by introducing a new reputation management model.