Releasing Private Contingency Tables

Main Article Content

Shubha U. Nabar
Nina Mishra

Abstract

Statistical agencies routinely publish aggregate data in the form of contingency tables.

In this paper, we consider the problem of releasing private contingency tables so that

the privacy of individual respondents in the table is preserved. We first uncover funda-

mental problems with existing cell suppression algorithms that are used for this purpose.

We then present a rigorous definition of privacy and a generic algorithmic framework

for cell suppression given this definition. Using this framework we build a complete

cell suppression solution for the special case of boolean private attributes. We study

both theoretically and experimentally the utility of our approach. Along the way, we

demonstrate a connection to the query auditing problem in statistical databases and

make a foundational contribution to this problem as well. In particular, we analyze an

unexamined assumption from the literature regarding the prior knowledge of attackers.

Article Details

How to Cite
Nabar, Shubha, and Nina Mishra. 2010. “Releasing Private Contingency Tables”. Journal of Privacy and Confidentiality 2 (1). https://doi.org/10.29012/jpc.v2i1.586.
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