A Bayesian Approach to Data Disclosure: Optimal Intruder Behavior for Continuous Data

Abstract

In this article we develop an approach to data disclosure in survey settings by adopting a probabilistic definition of disclosure due to Dalenius. Our approach is based on the principle that a data collection agency must consider disclosure from the perspective of an intruder in order to efficiently evaluate data disclosure limitation procedures. The probabilistic definition and our attempt to study optimal intruder behavior lead naturally to a Bayesian formulation. We apply the methods in a small-scale simulation study using data adapted from an actual survey conducted by the Institute for Social Research at York University.