Paper 2024/2037

Multilateral Trade Credit Set-off in MPC via Graph Anonymization and Network Simplex

Abstract

Multilateral Trade Credit Set-off (MTCS) is a process run by a service provider that collects trade credit data (i.e. obligations from a firm to pay another firm) from a network of firms and detects cycles of debts that can be removed from the system. The process yields liquidity savings for the participants, who can discharge their debts without relying on expensive loans. We propose an MTCS protocol that protects firms' sensitive data, such as the obligation amount or the identity of the firms they trade with. Mathematically, this is analogous to solving the Minimum Cost Flow (MCF) problem over a graph of $n$ firms, where the $m$ edges are the obligations. State-of-the-art techniques for Secure MCF have an overall complexity of $O(n^{10} \log n)$ communication rounds, making it barely applicable even to small-scale instances. Our solution leverages novel secure techniques such as Graph Anonymization and Network Simplex to reduce the complexity of the MCF problem to $O(max(n, \log\log{n+m}))$ rounds of interaction per pivot operations in which $O(max(n^2, nm))$ comparisons and multiplications are performed. Experimental results show the tradeoff between privacy and optimality.