Programming language techniques for differential privacy

Abstract

Differential privacy is rigorous framework for stating and enforcing privacy guarantees on computations over sensitive data. Informally, differential privacy ensures that the presence or absence of a single individual in a database has only a negligible statistical effect on the computation's result. Many specific algorithms have been proved differentially private, but manually checking that a given program is differentially private can be subtle, tedious, or both. This approach becomes unfeasible when larger programs are considered.