Grant / January 2020

Allegro: A Framework for Practical Differential Privacy of SQL Queries

Current approaches for data security and privacy fail to reconcile the seemingly contradictory goals of leveraging data for positive outcomes while guaranteeing privacy protection for individuals. One promising approach is differential privacy, which allows general statistical analysis of data while providing individuals with a strong formal guarantee of privacy. This research team will design and develop techniques for practical privacy-preserving data analytics, enabling the use of advanced mechanisms like differential privacy in the real world.