Publications

This article advocates a hybrid legal-technical approach to the evaluation of technical measures designed to render information anonymous in order to bring it outside the scope of data protection regulation. The article demonstrates how such an...

Studying problems of interest, like finding trends in medical data, can require analyzing data which contains sensitive and personally identifying information. As a result, it is often infeasible to release these datasets to researchers or to the general...

In this paper, we propose a programming framework for the library of dierentially private algorithms that will be at the core of the new OpenDP open-source software project (http://opendp.io/).

We initiate a study of the composition properties of interactive dierentially private mechanisms. An interactive dierentially private mechanism is an algorithm that allows an analyst to adaptively ask queries about a sensitive dataset, with the property...

There are significant gaps between legal and technical thinking around data privacy. Technical standards are described using mathematical language whereas legal standards are not rigorous from a mathematical point of view and often resort to concepts...

We study the problem of verifying differential privacy for loop-free programs with probabilistic choice. Programs in this class can be seen as randomized Boolean circuits, which we will use as a formal model to answer two different questions: first...