Managing trust in a peer-2-peer information system
Proceedings of the tenth international conference on Information and knowledge management
Choosing reputable servents in a P2P network
Proceedings of the 11th international conference on World Wide Web
Peer-to-Peer: Harnessing the Power of Disruptive Technologies
Peer-to-Peer: Harnessing the Power of Disruptive Technologies
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
A reputation system for peer-to-peer networks
NOSSDAV '03 Proceedings of the 13th international workshop on Network and operating systems support for digital audio and video
A survey of key management for secure group communication
ACM Computing Surveys (CSUR)
Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Limited reputation sharing in P2P systems
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Recommendation Retrieval in Reputation Assessment for Peer-to-Peer Systems
Electronic Notes in Theoretical Computer Science (ENTCS)
Reputation estimation and query in peer-to-peer networks
IEEE Communications Magazine
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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.