CIF: Small: Efficiency and Robustness of Secure Computation

Purdue University, West Lafayette IN

Investigators

Abstract

Secure multi-party computation (MPC) is a leading privacy-enhancing technology bridging the data utility and privacy chasm. MPC facilitates computing over private data without revealing non-essential information, meeting privacy expectations, and complying with regulatory privacy laws. MPC creates exciting collaboration opportunities in social, scientific, commercial, and security domains. This project aims to improve the security and efficiency of MPC, thereby increasing its adoption. The project's outcomes will have a significant real-world impact by guiding computer-assisted secure protocol design and automating threat assessment against side-channel attacks. Characterizing MPC's efficiency and robustness is in its infancy. Efficiency metrics like rate and capacity are natural in the cryptographic context. Quantitative investigations into the robustness of MPC against side-channel attacks and recovery from them are also well-motivated. This project builds a mathematical framework to determine the most efficient MPC protocols and their robustness to side-channel attacks. This theory for MPC rate, capacity, and robustness will be built at the intersection of computer science, information theory, and mathematics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.