PRobabilistic Epistemic Logic Applied to Privacy (PRELAP)
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
- Project Colloquium
- January 2020 : Kick-off meeting in Johannesburg
Open PhD position starting 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.
– a Master degree in Computer Science, Mathematics, or a relevant discipline has to be completed before October 1st, 2020.
– fluent written and spoken English
Candidates with an interdisciplinary background are particularly encouraged to apply. Previous knowledge of topics related to logic and/or privacy is an advantage. Knowledge of French language is not required. French courses are offered to PhD students if they desire to learn French during their thesis.
Please submit your application by email to Sabine Frittella (firstname.lastname@example.org) and Benjamin Nguyen (email@example.com) including:
– cover letter
– copies of the relevant certificates
– list of references
– relevant publications, if exist.
– Salary: the position is for three years (36 months), gross salary of 1768 € per month including health insurance. The PhD student will have the opportunity to teach which increases the gross salary by 220 € per month. – Location: Department of Computer Science at INSA Centre Val de Loire, Bourges, France
– Contacts: Dr Sabine Frittella (email: firstname.lastname@example.org) and Pr Benjamin Nguyen (email@example.com)
– Application deadline: March 31st, 2020 or until fulfilled
– Starting date: October 1st, 2020.
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