• DocumentCode
    2596744
  • Title

    A Fuzzy Trust Model with Punishment Mechanism

  • Author

    Lin, Huaiqing ; Hu, Zhengbin ; Zhou, Yonghong

  • Author_Institution
    Coll. of Electron. Eng., Naval Univ. of Eng., Wuhan, China
  • Volume
    2
  • fYear
    2010
  • fDate
    24-25 April 2010
  • Firstpage
    158
  • Lastpage
    161
  • Abstract
    One way to minimize threats in P2P system is to exploit reputation to help evaluate the trustworthiness and predict the future behaviors of peers. In this paper, a set of parameters are identified for describing the trust of a peer. And a trust model based on fuzzy techniques is presented. The trust model uses Amplifier of Malicious Behavior (AMB) to intensify malicious behaviors and helps peers identify the sly malicious peers. The recommendation credibility is evaluated by Recommendation Weight (RW) and Recommendation Accuracy (RA). In simulation, this trust model has been shown to improve the efficiency of P2P system by significantly decreasing the number of inauthentic files on the network.
  • Keywords
    belief networks; fuzzy logic; peer-to-peer computing; security of data; P2P system; amplifier of malicious behavior; fuzzy trust model; inauthentic files; peer behaviors; punishment mechanism; recommendation accuracy; recommendation credibility; recommendation weight; reputation systems; security threats; sly malicious peers; trustworthiness; Artificial neural networks; Computer networks; Educational institutions; Fuzzy logic; Fuzzy systems; Information security; Information technology; Peer to peer computing; Predictive models; Wireless communication; fuzzy logic; p2p; reputation; trust;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networks Security Wireless Communications and Trusted Computing (NSWCTC), 2010 Second International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-4011-5
  • Electronic_ISBN
    978-1-4244-6598-9
  • Type

    conf

  • DOI
    10.1109/NSWCTC.2010.173
  • Filename
    5480747