Toward Efficient and Secure Collaborative SQL Analyses of Billion-Scale Datasets

Designing an efficient and secure collaborative SQL analysis system that supports large-scale dataset inputs is a very challenging task. In this paper, we present FedQuery, an MPC-based solution for efficient and secure collaborative analysis that is able to handle billion-scale dataset inputs. FedQuery introduces novel designs in its system architecture, the underlying MPC primitives, and oblivious SQL operators as well as their combinations, significantly reducing communication and computation overhead. Comprehensive experiments on real-world datasets show that FedQuery achieves large performance improvements over state-of-the-art baselines at both the operator and query levels. Additionally, it can handle complex SQL queries on datasets up to ten billion entries in less than 14 hours.