Privacy-MaxEnt: Integrating background knowledge in privacy quantification

Wenliang Du, Zhouxuan Teng, Zutao Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

45 Scopus citations

Abstract

Privacy-Preserving Data Publishing (PPDP) deals with the publication of microdata while preserving people' private information in the data. To measure how much private information can be preserved, privacy metrics is needed. An essential element for privacy metrics is the measure of how much adversaries can know about an individual's sensitive attributes (SA) if they know the individual's quasi-identifters (QI), i.e., we need to measure P(SA/QI). Such a measure is hard to derive when adversaries' background knowledge has to be considered. We propose a systematic approach, Privacy-MaxEnt, to integrate background knowledge in privacy quantification. Our approach is based on the maximum entropy principle. We treat all the conditional probabilities P(SA | QI) as unknown variables; we treat the background knowledge as the constraints of these variables; in addition, we also formulate constraints from the published data. Our goal becomes finding a solution to those variables (the probabilities) that satisfy all these constraints. Although many solutions may exist, the most unbiased estimate of P(SA | QI) is the one that achieves the maximum entropy.

Original languageEnglish (US)
Title of host publicationSIGMOD 2008
Subtitle of host publicationProceedings of the ACM SIGMOD International Conference on Management of Data 2008
Pages459-472
Number of pages14
DOIs
StatePublished - Dec 10 2008
Event2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08 - Vancouver, BC, Canada
Duration: Jun 9 2008Jun 12 2008

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Other

Other2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08
CountryCanada
CityVancouver, BC
Period6/9/086/12/08

Keywords

  • Data publishing
  • Privacy quantification

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Du, W., Teng, Z., & Zhu, Z. (2008). Privacy-MaxEnt: Integrating background knowledge in privacy quantification. In SIGMOD 2008: Proceedings of the ACM SIGMOD International Conference on Management of Data 2008 (pp. 459-472). [1376665] (Proceedings of the ACM SIGMOD International Conference on Management of Data). https://doi.org/10.1145/1376616.1376665