Development and Analysis of Deterministic Privacy-Preserving Policies Using Non- Stochastic Information Theory

Abstract

A deterministic privacy metric using non-stochastic information theory is developed. Particularly, maximin information is used to construct a measure of information leakage, which is inversely proportional to the measure of privacy. Anyone can submit a query to a trusted agent with access to a non-stochastic uncertain private dataset. Optimal deterministic privacy-preserving policies for responding to the submitted query are computed by maximizing the measure of privacy subject to a constraint on the worst-case quality of the response (i.e., the worst-case difference between the response by the agent and the output of the query computed on the private dataset). The optimal privacy-preserving..