Privacy-preserving SQL queries on cross-organisation databases
Ye Han, Xiaojie Guo, Tong Li, Xiaotao Liu · International Journal of Computational Science and Engineering · 2024
In recent years, much industrial interest has been paid to SQL queries on a joint database contributed by several mutually distributed companies or organisations. However, privacy regulations and commercial interest prevent these entities to trivially share their local databases with each other. To enable such SQL queries, some privacy-preserving technologies should be applied. In this work, we outline a provably secure MPC framework of privacy-preserving SQL queries for industrial applications, such as medical research in hospitals, financial oversight, business cooperation, etc. In particular, this framework is secure against any semi-honest adversary, which is a popular threat model in real-life systems. This framework also models a common efficiency optimisation of SQL query plans at the cost of mild leakage.