Abstract
The issues of trust are especially of great importance in peer-to-peer electronic online communities [5]. One way to address these issues is to use community-based reputations to help estimate the trustworthiness of peers. This paper presents a reputation-based trust supporting framework which includes a mathematical trust model, a decentralized trust data dissemination scheme and a distributed implementation algorithm of the model over a structured P2P network. In our approach, each peer is assigned a unique trust value, computed by aggregating the similarity-filtered recommendations of the peers who have interacted with it. The similarity between peers is computed by a novel simplified method. We also elaborate on decentralized trust data management scheme ignored in existing solutions for reputation systems. Finally, simulation-based experiments show that the system based on our algorithm is robust even against attacks from groups of malicious peers deliberately cooperating to subvert it.
This work is supported by the National Natural Science Foundation of China (No. 60373021).
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© 2005 Springer-Verlag Berlin Heidelberg
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Li, J., Jing, Y., Fu, P., Zhang, G., Chen, Y. (2005). A Similarity-Based Recommendation Filtering Algorithm for Establishing Reputation-Based Trust in Peer-to-Peer Electronic Communities. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_151
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DOI: https://doi.org/10.1007/11596981_151
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30819-5
Online ISBN: 978-3-540-31598-8
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