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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3802 LNAI, pp. 1017–1024). Springer Verlag. https://doi.org/10.1007/11596981_151
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