NFGen: Automatic Non-linear Function Evaluation Code Generator for General-purpose MPC Platforms

TL;DR

NFGen is a versatile code generator that uses piecewise polynomial approximations to efficiently and accurately evaluate non-linear functions across various secure multi-party computation platforms.

Contribution

It introduces NFGen, a novel technique employing pre-computed polynomial approximations and a performance-prediction-based code generator for general-purpose MPC platforms.

Findings

Significant performance improvements over existing methods

High accuracy in non-linear function evaluation

Broad applicability across multiple MPC protocols and platforms

Abstract

Due to the absence of a library for non-linear function evaluation, so-called general-purpose secure multi-party computation (MPC) are not as ''general'' as MPC programmers expect. Prior arts either naively reuse plaintext methods, resulting in suboptimal performance and even incorrect results, or handcraft ad hoc approximations for specific functions or platforms. We propose a general technique, NFGen, that utilizes pre-computed discrete piecewise polynomials to accurately approximate generic functions using fixed-point numbers. We implement it using a performance-prediction-based code generator to support different platforms. Conducting extensive evaluations of 23 non-linear functions against six MPC protocols on two platforms, we demonstrate significant performance, accuracy, and generality improvements over existing methods.