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
Trust-based security for wireless ad hoc and sensor networks
Computer Communications
Taxonomy of trust: Categorizing P2P reputation systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
Towards adaptive security for convergent wireless sensor networks in beyond 3G environments
Wireless Communications & Mobile Computing - Wireless Technologies Advances for Emergency and Rural Communications
The agent reputation and trust (ART) testbed
iTrust'06 Proceedings of the 4th international conference on Trust Management
The design space of wireless sensor networks
IEEE Wireless Communications
Towards pre-standardization of trust and reputation models for distributed and heterogeneous systems
Computer Standards & Interfaces
TRIP, a trust and reputation infrastructure-based proposal for vehicular ad hoc networks
Journal of Network and Computer Applications
LFTM, linguistic fuzzy trust mechanism for distributed networks
Concurrency and Computation: Practice & Experience
Decision making matters: A better way to evaluate trust models
Knowledge-Based Systems
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Trust and reputation models research and development for distributed systems such as P2P networks, Wireless Sensor Networks (WSNs) or Multi-agent systems has arisen and taken importance in the last recent years among the international research community. However it is not always easy to check the correctness and accuracy of a model and even more, to compare it against other trust and reputation models. This paper presents TRMSim-WSN, a Java-based trust and reputation models simulator aimed to provide an easy way to test a trust and/or reputation model over WSNs and to compare it against other models. It allows the user to adjust several parameters such as the percentage of malicious nodes or the possibility of forming a collusion, among many others.