Privacy-enhanced reputation-feedback methods to reduce feedback extortion in online auctions

  • Authors:
  • Michael T. Goodrich;Florian Kerschbaum

  • Affiliations:
  • University of California, Irvine, Irvine, CA, USA;SAP Research, Karlsruhe, Germany

  • Venue:
  • Proceedings of the first ACM conference on Data and application security and privacy
  • Year:
  • 2011

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Abstract

In this paper, we study methods for improving the utility and privacy of reputation scores for online auctions, such as used in eBay, so as to reduce the effectiveness of feedback extortion. The main idea behind our techniques is to escrow reputations scores until appropriate external events occur. Depending on the degree of utility and privacy needed, these external techniques could depend on the number and type of reputation scores collected. Moreover, if additional privacy protection is needed, then random sampling can be used with respect reputation scores in such a way that reputation aggregates remain useful, but individual reputation scores are probabilistically hidden from users. Finally, we show that if privacy is also desired with respect to the the reputation aggregator, then we can use zero-knowledge proofs for reputation comparisons.