The general goal of research into privacy-preserving data analysis is to develop techniques that allow to get the best utility out of a dataset without violating the privacy of the individuals represented in it. This includes finding secure ways of providing public access to private datasets, securely decentralising services that rely on private data from individuals, enabling joint analysis on private data held by several organisations, and securely outsourcing computations on private data.
The goal of this project is to study the interplays between emerging privacy-enhancing technologies such as homomorphic encryption, differential privacy, and multi-party computation protocols, and implement scalable private data analysis algorithms with formal guarantees.
