Keep a Few: Outsourcing Data While Maintaining Confidentiality

  • Valentina Ciriani
  • Sabrina De Capitani di Vimercati
  • Sara Foresti
  • Sushil Jajodia
  • Stefano Paraboschi
  • Pierangela Samarati
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5789)

Abstract

We put forward a novel paradigm for preserving privacy in data outsourcing which departs from encryption. The basic idea behind our proposal is to involve the owner in storing a limited portion of the data, and maintaining all data (either at the owner or at external servers) in the clear. We assume a relational context, where the data to be outsourced is contained in a relational table. We then analyze how the relational table can be fragmented, minimizing the load for the data owner. We propose several metrics and present a general framework capturing all of them, with a corresponding algorithm finding a heuristic solution to a family of NP-hard problems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Valentina Ciriani
    • 1
  • Sabrina De Capitani di Vimercati
    • 1
  • Sara Foresti
    • 1
  • Sushil Jajodia
    • 2
  • Stefano Paraboschi
    • 3
  • Pierangela Samarati
    • 1
  1. 1.DTIUniversità degli Studi di MilanoCremaItalia
  2. 2.CSISGeorge Mason UniversityFairfaxUSA
  3. 3.DIIMMUniversità degli Studi di BergamoDalmineItalia

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