Paper 2022/332

CostCO: An automatic cost modeling framework for secure multi-party computation

Vivian Fang, Lloyd Brown, William Lin, Wenting Zheng, Aurojit Panda, and Raluca Ada Popa

Abstract

The last decade has seen an explosion in the number of new secure multi-party computation (MPC) protocols that enable collaborative computation on sensitive data. No single MPC protocol is optimal for all types of computation. As a result, researchers have created hybrid-protocol compilers that translate a program into a hybrid protocol that mixes different MPC protocols. Hybrid-protocol compilers crucially rely on accurate cost models, which are handwritten by the compilers' developers, to choose the correct schedule of protocols. In this paper, we propose CostCO, the first automatic MPC cost modeling framework. CostCO develops a novel API to interface with a variety of MPC protocols, and leverages domain-specific properties of MPC in order to enable efficient and automatic cost-model generation for a wide range of MPC protocols. CostCO employs a two-phase experiment design to efficiently synthesize cost models of the MPC protocol’s runtime as well as its memory and network usage. We verify CostCO’s modeling accuracy for several full circuits, characterize the engineering effort required to port existing MPC protocols, and demonstrate how hybrid-protocol compilers can leverage CostCO’s cost models.