A probabilistic perspective on re-identifiability

M.R. Koot, M.R.H. Mandjes, G. Noordende, van 't, C.T.A.M. Laat, de

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Abstract

A quasi-identifier is a set of attributes that can be used to re-identify entries in anonymized data sets. A group of individuals is considered about whom quasi-identifying numerical information is disclosed such as date of birth, age, weight, and height. The fraction of individuals is determined whose information is unique in that group and hence is identifiable unambiguously. Nonuniformity can be captured well by a single number, the Kullback-Leibler distance. For example sets of real microdata, given approximations based on Kullback-Leibler distances are accurate. Second, the effect of disclosing more specific or less specific information is analyzed experimentally. Third, the effect of correlation between numerical attributes is measured. A formula gives the re-identifiability level. The approximations are validated using publicly available demographic data sets. © 2013 Copyright Taylor and Francis Group, LLC. Keywords: data anonymity; demographic data; Kullback-Leibler distance; privacy; probability theory; security
Original languageEnglish
Pages (from-to)155-171
Number of pages17
JournalMathematical Population Studies
Volume20
Issue number3
DOIs
Publication statusPublished - 2013

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