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On Mining Sensitive Rules to Identify Privacy Threats

  • Irene Díaz
  • Luis J. Rodríguez-Mũniz
  • Luigi Troiano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

Data mining techniques represent a useful tool to cope with privacy problems. In this work an association rule mining algorithm adapted to the privacy context is developed. The algorithm produces association rules with a certain structure (the premise set is a subset of the public features of a released table while the consequent is the feature to protect). These rules are then used to reveal and explain relationships from data affected by some kind of anonymization process and thus, to detect threats.

Keywords

disclosure control association rules data privacy anonymity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Irene Díaz
    • 1
  • Luis J. Rodríguez-Mũniz
    • 2
  • Luigi Troiano
    • 3
  1. 1.Computer Science DepartmentUniversity of OviedoSpain
  2. 2.Department of Statistics and O.R.University of OviedoSpain
  3. 3.Department of EngineeringUniversity of SannioItaly

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