A similarity-based recommendation filtering algorithm for establishing reputation-based trust in peer-to-peer electronic communities

0Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

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. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free