Privacy

Objectifs pédagogiques

The objective of this course is to give to students a hands-on introduction to the main issues faced by these techniques and to the diversity of solutions found for reaching valuable privacy/utility tradeoffs in real life.

Description du cours

« Personal data is the new oil of the internet and the new currency of the digital world. » claimed Meglena Kouneva, European Commissioner for Consumer Protection in March 2009. The value of personal data for industry, science and society in general is widely recognized today. However, the potentially identifying and sensitive nature of personal data is often a major obstacle to their collection, processing, and sharing. The goal of privacy-preserving techniques in data-centric systems is precisely to enable a wide diversity of usages of big personal data while still providing strong privacy guarantees.

Contenu du cours

  • Introduction : données personnelles et société aujourd’hui, motivation du besoin de les protéger.
  • Publication de données respectueuse de la vie privée (anonymisation) : modèles et algorithmes par partitionnement, modèles et algorithmes type differential privacy
  • Pistage sur le Web : cookies, empreintes navigateur, contre-mesures.
  • Contrôle d’accès dans les bases de données : DAC, RBAC, MAC
  • Recherche d’informations respectueuse de la vie privée : PIR computationelle et PIR théorie de l’information
  • Interrogation de données personnelles chiffrées : approches serveur, approches client
  • Introduction au RGPD
  • Introduction aux arênes de standardisation du Web orientées privacy

Mots-clés

Privacy, partial information leakage, differential privacy, encryption, personal data.

Prérequis

  • Basics in the Python programing language
  • Basic knowledge in cryptography
  • Basic skills in statistics and probabilities

Bibliographie

  • Privacy-Preserving Data Publishing by Bee-Chung Chen, Daniel Kifer, Kristen LeFevre and Ashwin Machanavajjhala, 2009.
  • The Algorithmic Foundations of Differential Privacy, by Cynthia Dwork and Aaron Roth, 2014.
  • Foundations of Cryptography: Volume 2, Basic Applications, by Oded Goldreich, 2004

Biographie de l’enseignant

Tristan Allard (responsible and main teacher) and teaching assistants for the technical part of the course, and external experts for the legal part.

« I am an associate professor (« maître de conférences ») since September 2014 at the Univ Rennes, CNRS, Irisa. I am also a fixed term (March 2020 to March 2023) associate professor (« professeur associé ») at the Université du Québec à Montréal (for co-supervising a joint PhD thesis between UQAM and UR1). Before that, I was a postdoctoral researcher at the Inria Zenith team in Montpellier. I conducted my Ph.D. thesis in Computer Science in the Inria SMIS team and received it from the University of Versailles in December 2011. The volume, variety, and velocity of digital personal data are increasing at a fast pace. Enabling both daily uses and large-scale analysis of personal data while preserving individuals’ privacy is a key challenge in building a knowledge society. My research interests lie within this wide field. I am particularly interested in the combination of differential privacy with cryptography (privacy-preserving data querying, privacy-preserving crowdsourcing, privacy-preserving data mining). And recently I got diverted by the study of browser fingerprints for web authentication. »