Privug: Using Probabilistic Programming for Quantifying Leakage in Privacy Risk Analysis

Raúl Pardo, Willard Rafnsson, Christian Probst, Andrzej Wasowski

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstrakt

Disclosure of data analytics results has important scientific and commercial justifications. However, no data shall be disclosed without a diligent investigation of risks for privacy of subjects. Privug is a tool-supported method to explore information leakage properties of data analytics and anonymization programs. In Privug, we reinterpret a program probabilistically, using off-the-shelf tools for Bayesian inference to perform information-theoretic analysis of the information flow. For privacy researchers, Privug provides a fast, lightweight way to experiment with privacy protection measures and mechanisms. We show that Privug is accurate, scalable, and applicable to a range of leakage analysis scenarios.
OriginalsprogEngelsk
TitelEuropean Symposium on Research in Computer Security : Computer Security – ESORICS 2021
Vol/bind12973
ForlagSpringer
Publikationsdato2021
ISBN (Trykt)978-3-030-88427-7
ISBN (Elektronisk)978-3-030-88428-4
DOI
StatusUdgivet - 2021
NavnLecture Notes in Computer Science
Vol/bind12973
ISSN0302-9743

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