Probabilistic privacy analysis of published views

Hui Wang, Laks V.S. Lakshmanan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Among techniques for ensuring privacy in data publishing, k-anonymity and publishing of views on private data are quite popular. In this paper, we consider data publishing by views and develop a probability framework for the analysis of privacy breach. We propose two attack models and derive the probability of privacy breach for each model.

Original languageEnglish
Title of host publicationProceedings of the 5th ACM Workshop on Privacy in Electronic Society, WPES 2006, Co-located with the 13th ACM Conference on Computer and Communications Security, CCS 2006
Pages81-84
Number of pages4
DOIs
StatePublished - 2006
Event5th ACM Workshop on Privacy in Electronic Society, WPES 2006, Co-located with the 13th ACM Conference on Computer and Communications Security, CCS 2006 - Alexandria, VA, United States
Duration: 30 Oct 200630 Oct 2006

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference5th ACM Workshop on Privacy in Electronic Society, WPES 2006, Co-located with the 13th ACM Conference on Computer and Communications Security, CCS 2006
Country/TerritoryUnited States
CityAlexandria, VA
Period30/10/0630/10/06

Keywords

  • privacy breach
  • private association
  • probabilistic analysis
  • published views

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