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CCS2022Top-tier venue

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

Xiaoyu Fan, Kun Chen, Guosai Wang, Mingchun Zhuang, Yi Li, Wei Xu

2022Year
9Citations
5Top-tier citations

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 1 , 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. CCS CONCEPTS • Security and privacy → Security services.

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