Section: Research Program

Research Program

To tackle the challenge introduced above, we identify four main lines of research:

• (Axis 1) Personal cloud server architectures. Based on the intuition that user control, security and privacy are key properties in the definition of trusted personal cloud solutions, our objective is to propose new architectures (encompassing both software and hardware aspects) for secure personal cloud data management and formally prove important bricks of the architecture.

• (Axis 2) Privacy preserving administration models and enforcement. This research axis is devoted to the definition of sharing rules that are easily manageable for the individual and enforced by default (i.e., secure implementation). Complementary to the definition of sharing policies, it is mandatory to help the average user regulate the complete lifecycle of her data, from its capture, to its dissemination and up to its deletion. Our objective is to propose new data administration models reaching the main requirements of a personal cloud (decentralized access and usage control models, data sharing, data collection and retention models, etc.) and study the enforcement of the resulting privacy policies based on secure hardware and formally proven architectural components.

• (Axis 3) Global query evaluation. The goal of this line of research is to provide capabilities for crossing data belonging to multiple individuals (e.g., performing statistical queries over personal data, computing queries on social graphs or organizing participatory data collection) in a fully decentralized setting while providing strong and personalized privacy guarantees. This means proposing new secure distributed database indexing models, privacy preserving query processing strategies and data anonymization techniques for the personal cloud.

• (Axis 4) Economic, legal and societal issues. This research axis is more transversal and entails multidisciplinary research, addressing the links between economic, legal, societal and technological aspects. We will follow here a multi-disciplinary approach based on a 3-step methodology: i) identifying important common issues related to privacy and to the exploitation of personal data; ii) characterizing their dimensions in all relevant disciplines and jointly study their entanglement; iii) validating the proposed analysis, models and trade-offs thanks to in vivo experiments.

These contributions will also rely on tools (algorithms, protocols, proofs, etc.) from other communities, namely security (cryptography, secure multiparty computations, formal methods, differential privacy, etc.) and distributed systems (distributed hash tables, gossip protocols, etc.). Beyond the research actions, we structure our software activity around a single common platform (rather than isolated demonstrators), integrating our main research contributions, called PlugDB. This platform is the cornerstone to help validating our research results through accurate performance measurements on a real platform, a common practice in the DB community, and target the best conferences. It is also a strong vector to federate the team, simplify the bootstrapping of new PhD or master students, conduct multi-disciplinary research and open the way to industrial collaborations and technological transfers.