PRobabilistic Epistemic Logic Applied to Privacy
The recently adopted General Data Protection Regulation (GDPR) drastically enforces legislation concerning EU citizen privacy. It massively increases penalties imposed to companies using information systems not protecting privacy. Hence, privacy enforcement is becoming critical for companies.
Privacy enforcement is a major scientific challenge. Indeed, estimating privacy exposure implies to be able to 1) model knowledge a curious attacker can obtain and 2) determine what he can infer from it. Probabilistic epistemic logic is a tool specifically designed to describe and reason about probabilistic knowledge such as “the attacker knows with probability p that agent A knows secret S”.
In this project, we use probabilistic epistemic logic and its proof theory to automatically prove privacy ensured by a system can be violated by an attacker or a system design protects privacy. We develop tools (mathematical and software ones) based on probabilistic epistemic logic for designing and auditing privacy protection of a system. Our two case studies are minimal exposure of personal data and privacy in social networks.
The project gather researchers from:
- Université de Versailles
- CEA LIST
- Utrecht University (the Netherlands)
- University of The Witwatersrand (South Africa)
- Chapman University (USA)
- Czech Academy of Sciences
- February 17-18, 2022: Workshop on Non-Classical Logic and Probabilistic Reasoning
- January 2020 : Kick-off meeting in Johannesburg
PhD position started October 1st, 2020.
The PhD candidate will work under the supervision of Sabine Frittella and Benjamin Nguyen within the team Security of Data and Systems. The aim of this PhD is to develop probabilistic formal methods for privacy. Depending on the interests of the applicant, the PhD could be either oriented mostly toward logic or mostly toward privacy. Logic-based research includes developing epistemic/probabilistic/many-valued logics to formalize reasoning, privacy, algorithms and attacks with logics. Privacy-based research includes studying and modelling privacy issues such as limiting privacy exposure during data collection and privacy policies on social networks.
Project leader: Sabine Frittella, Maîtresse de Conférence, INSA CVL, LIFO lab, SDS team
- email: firstname.lastname@example.org
- address: INSA CVL, 88 boulevard Lahittolle, 18022 Bourges Cedex FRANCE