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Privacy-Preserving Distributed k-Anonymity

  • Wei Jiang
  • Chris Clifton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3654)

Abstract

k-anonymity provides a measure of privacy protection by preventing re-identification of data to fewer than a group of k data items. While algorithms exist for producing k-anonymous data, the model has been that of a single source wanting to publish data. This paper presents a k-anonymity protocol when the data is vertically partitioned between sites. A key contribution is a proof that the protocol preserves k-anonymity between the sites: While one site may have individually identifiable data, it learns nothing that violates k-anonymity with respect to the data at the other site. This is a fundamentally different distributed privacy definition than that of Secure Multiparty Computation, and it provides a better match with both ethical and legal views of privacy.

Keywords

k-anonymity privacy security 

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Copyright information

© IFIP International Federation for Information Processing 2005

Authors and Affiliations

  • Wei Jiang
    • 1
  • Chris Clifton
    • 1
  1. 1.Department of Computer SciencePurdue UniversityWest LafayetteUSA

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