Secure Multiparty Computation (MPC)

Protocols for secure multiparty computation (MPC) enable a set of parties to interact and compute a joint function of their private inputs while revealing nothing but the output. The potential applications for MPC are huge: privacy-preserving auctions, private DNA comparisons, private machine learning, threshold cryptography, and more. Due to this, MPC has been an intensive topic of research in academia ever since it was introduced in the 1980s by Yao for the two-party case (FOCS 1986), and by Goldreich, Micali and Wigderson for the multiparty case (STOC 1987). Recently, MPC has become efficient enough to be used in practice, and has made the transition from an object of theoretical study to a technology being used in industry. In this article, we will review what MPC is, what problems it solves, and how it is being currently used. We note that the examples and references brought in this review article are far from comprehensive, and due to the lack of space many highly relevant works are not cited