Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
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
Supporting Trust in Virtual Communities
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6 - Volume 6
PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing
IEEE Transactions on Parallel and Distributed Systems
A survey of trust in computer science and the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Trust and nuanced profile similarity in online social networks
ACM Transactions on the Web (TWEB)
P2P reputation management: Probabilistic estimation vs. social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
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The growing of networks and the success of fully distributed mechanisms and protocols to exchange data - as peer-to-peer networks - emphasise the need of trustworthiness. Usually both trust and reputation are taken into account: the former expresses the direct experience, whereas the latter represents the common opinion of the whole network. Their applicability and usefulness however could become uncertain when some node of the network is fraudulent, i.e. reports false opinion in order to enhance/reduce the reputation of someone else. In this paper we argue an algorithm - that takes inspiration from the secure Eigen-Trust - aiming at reducing the impact of such fraudulent nodes. We report some preliminary results of simulations performed on Advogato and SqueakFoundation datasets.