A holistic mechanism against file pollution in peer-to-peer networks

  • Authors:
  • Zhuhua Cai;Ruichuan Chen;Jianqiao Feng;Cong Tang;Zhong Chen;Jianbin Hu

  • Affiliations:
  • Peking University, Ministry of Education, China;Peking University, Ministry of Education, China;Peking University, Ministry of Education, China;Peking University, Ministry of Education, China;Peking University, Ministry of Education, China;Peking University, Ministry of Education, China

  • Venue:
  • Proceedings of the 2009 ACM symposium on Applied Computing
  • Year:
  • 2009

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Abstract

Content pollution is pervasive in the current peer-to-peer file sharing systems. Many previous reputation models have been proposed to address this problem, however, such models strongly rely on the participants' feedback. In this paper, we bring forward a new holistic mechanism which integrates the reputation model, inherent file-source-based information and the statistical data reflecting the diffusion state to defend against pollution attack. First, we deploy a redundancy mechanism to assure that the file requester receives the correct indices that accord with the information published by the file provider. Second, we complement the reputation information with the diffusion data to help the file requester select the authentic file for downloading. Finally, we introduce a block-oriented probabilistic verification protocol to help the file requester discern the polluted files during the downloading with a low cost. We perform a simulation which shows that our holistic mechanism can perform very well and converge to a high accuracy rapidly, even in a highly malicious environment.