Conference Proceedings

Non-Stochastic Hypothesis Testing with Application to Privacy Against Hypothesis-Testing Adversaries

F Farokhi

Proceedings of the ... IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control | IEEE | Published : 2020

Abstract

We consider privacy against hypothesis-testing adversaries within a non-stochastic framework. We develop a theory of non-stochastic hypothesis testing by borrowing the notion of uncertain variables from non-stochastic information theory. We define tests as binary-valued mappings on uncertain variables and prove a fundamental bound on the performance of tests in non-stochastic hypothesis testing. We use this bound to develop a measure of privacy. We then construct reporting policies with prescribed privacy and utility guarantees. The utility of a reporting policy is measured by the distance between reported and original values. We illustrate the effects of using such privacy-preserving report..

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