Privacy-aware Distributed Hypothesis Testing
Sreejith Sreekumar, Asaf Cohen, Deniz G\"und\"uz

TL;DR
This paper investigates the trade-offs between communication rate, hypothesis testing accuracy, and privacy in a distributed setting, providing theoretical bounds and characterizations for privacy-aware hypothesis testing.
Contribution
It introduces single-letter bounds and characterizations for privacy-utility trade-offs in distributed hypothesis testing with privacy constraints.
Findings
Established inner bounds on rate-error exponent-privacy trade-offs.
Derived single-letter characterizations for specific testing scenarios.
Showed the strong converse does not hold under privacy constraints.
Abstract
A distributed binary hypothesis testing (HT) problem involving two parties, a remote observer and a detector, is studied. The remote observer has access to a discrete memoryless source, and communicates its observations to the detector via a rate-limited noiseless channel. The detector observes another discrete memoryless source, and performs a binary hypothesis test on the joint distribution of its own observations with those of the observer. While the goal of the observer is to maximize the type II error exponent of the test for a given type I error probability constraint, it also wants to keep a private part of its observations as oblivious to the detector as possible. Considering both equivocation and average distortion under a causal disclosure assumption as possible measures of privacy, the trade-off between the communication rate from the observer to the detector, the type II…
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