activity
20162026
most citedPointwise Maximal Leakage

29 citations · 59 across the 15 of their papers we have counts for

collaborators

16 papers

cs.IT2026

Empirical coordination in the finite blocklength regime: an achievability result---Extended version

Olivier Massicot, Giulia Cervia, Maël Le Treust

Empirical coordination offers a way to understand how agents can coordinate actions under communication constraints. This paper investigates the finite blocklength regime of this p…

cs.CR2025

Image selective encryption analysis using mutual information in CNN based embedding space

Ikram Messadi, Giulia Cervia, Vincent Itier

As digital data transmission continues to scale, concerns about privacy grow increasingly urgent - yet privacy remains a socially constructed and ambiguously defined concept, lacki…

cs.IT2023

Pointwise Maximal Leakage on General Alphabets

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering +1

Pointwise maximal leakage (PML) is an operationally meaningful privacy measure that quantifies the amount of information leaking about a secret to a single outcome of a related…

cs.CR2023★ 1 cited

Rethinking Disclosure Prevention with Pointwise Maximal Leakage

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering +1

This paper introduces a paradigm shift in the way privacy is defined, driven by a novel interpretation of the fundamental result of Dwork and Naor about the impossibility of absolu…

cs.IT2022★ 29 cited

Pointwise Maximal Leakage

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering +1

We introduce a privacy measure called pointwise maximal leakage, generalizing the pre-existing notion of maximal leakage, which quantifies the amount of information leaking about a…

cs.IT2021

Optimal Maximal Leakage-Distortion Tradeoff

Sara Saeidian, Giulia Cervia, Tobias J. Oechtering +1

Most methods for publishing data with privacy guarantees introduce randomness into datasets which reduces the utility of the published data. In this paper, we study the privacy-uti…