Maximal Guesswork Leakage
Abstract
We introduce the study of information leakage through \emph{guesswork}, the minimum expected number of guesses required to guess a random variable. In particular, we define \emph{maximal guesswork leakage} as the multiplicative decrease, upon observing , of the guesswork of a randomized function of , maximized over all such randomized functions. We also study a pointwise form of the leakage which captures the leakage due to the release of a single realization of . We also study these two notions of leakage with oblivious (or memoryless) guessing. We obtain closed-form expressions for all these leakage measures, with the exception of one. Specifically, we are able to obtain closed-form expression for maximal guesswork leakage for the binary erasure source only; deriving expressions for arbitrary sources appears challenging. Some of the consequences of our results are -- a connection between guesswork and differential privacy and a new operational interpretation to maximal -leakage in terms of guesswork.
Keywords
Cite
@article{arxiv.2405.02585,
title = {Maximal Guesswork Leakage},
author = {Gowtham R. Kurri and Malhar Managoli and Vinod M. Prabhakaran},
journal= {arXiv preprint arXiv:2405.02585},
year = {2024}
}
Comments
6 pages. Extended version of a paper accepted to ISIT 2024