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

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationEuropean Symposium on Research in Computer Security : Computer Security – ESORICS 2021
Publication date2021
ISBN (Print)978-3-030-88427-7
ISBN (Electronic)978-3-030-88428-4
Publication statusPublished - 2021
SeriesLecture Notes in Computer Science


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