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

  • Authors:

  • Jingtao Li;Yinan Jing;Peng Fu;Gendu Zhang;Yongqiang Chen

  • Affiliations:

  • Department of Computer and Information Technology, Fudan University, Shanghai, China;Department of Computer and Information Technology, Fudan University, Shanghai, China;Network Institute, School of Electronic and Information Engineering Xi’an Jiaotong University, Xi’an, China;Department of Computer and Information Technology, Fudan University, Shanghai, China;School of Information Science and Engineering, Lanzhou University, Lanzhou, China

  • Venue:
  • CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
  • Year:
  • 2005

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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.