The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
TrustGuard: countering vulnerabilities in reputation management for decentralized overlay networks
WWW '05 Proceedings of the 14th international conference on World Wide Web
PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing
IEEE Transactions on Parallel and Distributed Systems
A Distributed Trust-based Reputation Model in P2P System
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01
A Trust-Enhanced Topology Adaptation Protocol for Unstructured P2P Overlays
SKG '07 Proceedings of the Third International Conference on Semantics, Knowledge and Grid
GossipTrust for Fast Reputation Aggregation in Peer-to-Peer Networks
IEEE Transactions on Knowledge and Data Engineering
Free Riding in Peer-to-Peer Networks
IEEE Internet Computing
A new evidential trust model for open communities
Computer Standards & Interfaces
Reputation management algorithms for DHT-based peer-to-peer environment
Computer Communications
Poisonedwater: An improved approach for accurate reputation ranking in P2P networks
Future Generation Computer Systems
Authentication and access control in RFID based logistics-customs clearance service platform
International Journal of Automation and Computing
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It is necessary to construct an effective trust model to build trust relationship between peers in peer-to-peer (P2P) network and enhance the security and reliability of P2P systems. The current trust models only focus on the consumers' evaluation to a transaction, which may be abused by malicious peers to exaggerate or slander the provider deliberately. In this paper, we propose a novel trust model based on mutual evaluation, called METrust, to suppress the peers' malicious behavior, such as dishonest evaluation and strategic attack. METrust considers the factors including mutual evaluation, similarity risk, time window, incentive, and punishment mechanism. The trust value is composed of the direct trust value and the recommendation trust value. In order to inhibit dishonest evaluation, both participants should give evaluation information based on peers' own experiences about the transaction while computing the direct trust value. In view of this, the mutual evaluation consistency factor and its time decay function are proposed. Besides, to reduce the risk of computing the recommendation trust based on the recommendations of friend peers, the similarity risk is introduced to measure the uncertainty of the similarity computing, while similarity is used to measure credibility. The experimental results show that METrust is effective, and it has advantages in the inhibition of the various malicious behaviors.