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 privacypreserving 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.

FLUTE: Fast and Secure Lookup Table Evaluations

“…While using large amounts of user data creates new possibilities, such as in the health industry and for machine learning [64], doing so plainly compromises users' privacy to the point where it might even be against the law because of regulations like the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act [42], [84]. Secure multi-party computation techniques (MPC) [39], [88] have demonstrated their ability to address this problem efficiently in a variety of real-world applications, including financial services [7], epidemiological modeling [41], privacypreserving machine learning [13], [24], [43], [51], [55],…”

Concretely efficient secure multi-party computation protocols: survey and more

“…We refer the reader to [16,17] for more MPC libraries and the comparison of known libraries. Many applications can be built upon MPC to protect the privacy of data, including machine learning (see, e.g., [18][19][20][21][22][23][24][25][26][27][28][29][30][31] and references therein), federated learning (see, e.g., [32][33][34][35][36]), data mining [37][38][39][40], auction [41][42][43], genomic analysis [44][45][46], securing databases (see [47] and references therein), and blockchain [48][49][50][51][52][53]. In addition, some techniques underlying MPC protocols can also be used to construct non-interactive zero-knowledge (ZK) proofs [54][55][56][57][58][59][60][61] based on the MPC-in-thehead paradigm, scalable ZK proofs…”