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Computer Science > Information Theory

Title: 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 $Y$, of the guesswork of a randomized function of $X$, 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 $Y$. 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 $\alpha$-leakage in terms of guesswork.
Comments: 6 pages. Extended version of a paper accepted to ISIT 2024
Subjects: Information Theory (cs.IT)
Cite as: arXiv:2405.02585 [cs.IT]
  (or arXiv:2405.02585v1 [cs.IT] for this version)

Submission history

From: Gowtham Raghunath Kurri [view email]
[v1] Sat, 4 May 2024 06:52:59 GMT (17kb)

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