Preserving the confidentiality of categorical statistical data bases when releasing information for association rules

Stephen E. Fienberg, Aleksandra B. Slavkovic

Research output: Contribution to journalReview article

27 Citations (Scopus)

Abstract

In the statistical literature, there has been considerable development of methods of data releases for multivariate categorical data sets, where the releases come in the form of marginal tables corresponding to subsets of the categorical variables. Very recently some of the ideas have been extended to allow for the release of combinations of mixtures of marginal tables and conditional tables for subsets of variables. Association rules can be viewed as conditional tables. In this paper we consider possible inferences an intruder can make about confidential categorical data following the release of information on one or more association rules. We illustrate this with several examples.

Original languageEnglish (US)
Pages (from-to)155-180
Number of pages26
JournalData Mining and Knowledge Discovery
Volume11
Issue number2
DOIs
StatePublished - Sep 1 2005

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Association rules

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

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Preserving the confidentiality of categorical statistical data bases when releasing information for association rules. / Fienberg, Stephen E.; Slavkovic, Aleksandra B.

In: Data Mining and Knowledge Discovery, Vol. 11, No. 2, 01.09.2005, p. 155-180.

Research output: Contribution to journalReview article

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