English

Maximal Guesswork Leakage

Information Theory 2024-05-07 v1 math.IT

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 YY, of the guesswork of a randomized function of XX, 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 YY. 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 α\alpha-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

R2 v1 2026-06-28T16:16:30.215Z