Privacy Preserving Record Matching Using Automated Semi-trusted Broker

  • Ibrahim Lazrig
  • Tarik Moataz
  • Indrajit Ray
  • Indrakshi Ray
  • Toan Ong
  • Michael Kahn
  • Frédéric Cuppens
  • Nora Cuppens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9149)

Abstract

In this paper, we present a novel scheme that allows multiple data publishers that continuously generate new data and periodically update existing data, to share sensitive individual records with multiple data subscribers while protecting the privacy of their clients. An example of such sharing is that of health care providers sharing patients’ records with clinical researchers. Traditionally, such sharing is performed by sanitizing personally identifying information from individual records. However, removing identifying information prevents any updates to the source information to be easily propagated to the sanitized records, or sanitized records belonging to the same client to be linked together. We solve this problem by utilizing the services of a third party, which is of very limited capabilities in terms of its abilities to keep a secret, secret, and by encrypting the identification part used to link individual records with different keys. The scheme is based on strong security primitives that do not require shared encryption keys.

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Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Ibrahim Lazrig
    • 1
  • Tarik Moataz
    • 1
    • 2
  • Indrajit Ray
    • 1
  • Indrakshi Ray
    • 1
  • Toan Ong
    • 3
  • Michael Kahn
    • 3
  • Frédéric Cuppens
    • 2
  • Nora Cuppens
    • 2
  1. 1.Department of Computer ScienceColorado State UniversityFord CollinsUSA
  2. 2.Institut Mines-TélécomTélécom BretagneCesson SévignéFrance
  3. 3.Anschutz Medical CampusUniversity of ColoradoDenverUSA

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