Abstract
It is difficult for data analysts to successfully incorporate differential privacy into their applications. Simple techniques are easily implemented but often yield high error rates. While sophisticated techniques exist, the analyst must not only find them in the vast privacy literature, but implement them carefully or privacy may be lost.
This talk describes efforts to make privacy technology more accessible, including work on benchmarks (DPComp) and privacy platforms (Ektelo and PrivateSQL). Benchmarks like DPComp facilitate comparison of state-of-the-art techniques and illuminate privacy-utility trade offs, increasing the transparency of privacy algorithms. Ektelo is a framework that allows analysts to author customized workflows from a collection of privacy-vetted "operators" that embody useful design patterns from the literature. PrivateSQL allows analysts to choose a privacy policy appropriate for their multi-relational schema and then write standard SQL queries, which are automatically rewritten to achieve the desired privacy semantics.