Data decoys for confidentiality in a distributed computation: matrix multiplication

  • Authors:

  • Tobin Jackson;Delbert Hart

  • Affiliations:

  • University of Alabama in Huntsville;University of Alabama in Huntsville

  • Venue:
  • ACM-SE 42 Proceedings of the 42nd annual Southeast regional conference
  • Year:
  • 2004

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Abstract

The confidentiality of a distributed computation can be compromised if trust in the client machines cannot be assured. Strategically placed decoy data can provide a measure of confidentiality to a distributed computation by overwhelming an attacker with the combinatorial problem of differentiating live data from decoy data. This paper explores the nature of using decoy data in general and considers the particular problem of using data decoys to provide confidentiality in a matrix multiplication distributed computation.