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Resisting Sybils in Peer-to-peer Markets

  • Jonathan Traupman
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 238)

Abstract

We describe two techniques for reducing the effectiveness of sybil attacks, in which an attacker uses a large number of fake user accounts to increase his reputation. The first technique uses a novel transformation of the ranks returned by the PageRank system. This transformation not only reduces susceptibility to sybil attacks but also provides an intuitive and easily interpreted reputation score. The second technique, called RAW, eliminates remaining vulnerabilities and allows full personalization of reputations, a necessary condition for a sybilproof reputation system.

Keywords

Random Walk Reputation System Outgoing Link High Reputation PageRank Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Jonathan Traupman
    • 1
  1. 1.Computer Science DivisionUniversity of CaliforniaBerkeley

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