Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata

Authors:
Josep M. Mateo-Sanz;Josep Domingo-Ferrer;Francesc Sebé
Affiliations:
Department of Computer Engineering and Mathematics, Rovira i Virgili University of Tarragona, Tarragona, Spain E-43007;Department of Computer Engineering and Mathematics, Rovira i Virgili University of Tarragona, Tarragona, Spain E-43007;Department of Computer Engineering and Mathematics, Rovira i Virgili University of Tarragona, Tarragona, Spain E-43007
Venue:
Data Mining and Knowledge Discovery
Year:
2005

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Abstract

Inference control for protecting the privacy of microdata (individual data) should try to optimize the tradeoff between data utility (low information loss) and protection against disclosure (low disclosure risk). Whereas risk measures are bounded between 0 and 1, information loss measures proposed in the literature for continuous data are unbounded, which makes it awkward to trade off information loss for disclosure risk. We propose in this paper to use probabilities to define bounded information loss measures for continuous microdata.