Private Liquidity Matching Using MPC

Abstract

Many central banks, as well as blockchain systems, are looking into distributed versions of interbank payment systems, in particular the netting procedure. When executed in a distributed manner this presents a number of privacy problems. This paper studies a privacy-preserving netting protocol to solve the gridlock resolution problem in such Real Time Gross Settlement systems. Our solution utilizes Multiparty Computation and is implemented in the SCALE MAMBA system, using Shamir secret sharing scheme over three parties in an actively secure manner. Our experiments show that, even for large throughput systems, such a privacy-preserving operation is often feasible.