The applicability of the perturbation based privacy preserving data mining for real-world data

  • Authors:
  • Li Liu;Murat Kantarcioglu;Bhavani Thuraisingham

  • Affiliations:
  • Computer Science Department, University of Texas at Dallas, Richardson, TX 75080, USA;Computer Science Department, University of Texas at Dallas, Richardson, TX 75080, USA;Computer Science Department, University of Texas at Dallas, Richardson, TX 75080, USA

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2008

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Abstract

When releasing microdata for research purposes, one needs to preserve the privacy of respondents while maximizing data utility. An approach that has been studied extensively in recent years is to use anonymization techniques such as generalization and ...