Disclosure Analysis for Two-Way Contingency Tables

  • Haibing Lu
  • Yingjiu Li
  • Xintao Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4302)


Disclosure analysis in two-way contingency tables is important in categorical data analysis. The disclosure analysis concerns whether a data snooper can infer any protected cell values, which contain privacy sensitive information, from available marginal totals (i.e., row sums and column sums) in a two-way contingency table. Previous research has been targeted on this problem from various perspectives. However, there is a lack of systematic definitions on the disclosure of cell values. Also, no previous study has been focused on the distribution of the cells that are subject to various types of disclosure. In this paper, we define four types of possible disclosure based on the exact upper bound and/or the lower bound of each cell that can be computed from the marginal totals. For each type of disclosure, we discover the distribution pattern of the cells subject to disclosure. Based on the distribution patterns discovered, we can speed up the search for all cells subject to disclosure.


Contingency Table Statistical Database Protected Cell Exact Bound Marginal Total 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Haibing Lu
    • 1
  • Yingjiu Li
    • 1
  • Xintao Wu
    • 2
  1. 1.Singapore Management UniversitySingapore
  2. 2.University of North Carolina at CharlotteCharlotteUSA

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