Assessing the disclosure risk of CTA-like methods

Abstract

Minimum distance controlled tabular adjustment (CTA) is a recent perturbative approach for statistical disclosure control in tabular data. CTA looks for the closest safe table, using some particular distance. In this talk we provide empirical results to assess the disclosure risk of the method. A set of 33 instances from the literature and four different attacker scenarios are considered. The result s show that, unless the attacker has good information about the original table, CTA has low disclosure risk. This talk summarizes results reported in the paper “Castro, J. (2013). On assessing the disclosure risk of controlled adjustment methods for statistical tabular data, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 20, 921–941.