GPU and CPU parallelization of honest-but-curious secure two-party computation

Nathaniel Husted, Steven Myers, Abhi Shelat, Paul Grubbs
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引用次数: 51

Abstract

Recent work demonstrates the feasibility and practical use of secure two-party computation [5, 9, 15, 23]. In this work, we present the first Graphical Processing Unit (GPU)-optimized implementation of an optimized Yao's garbled-circuit protocol for two-party secure computation in the honest-but-curious and 1-bit-leaked malicious models. We implement nearly all of the modern protocol advancements, such as Free-XOR, Pipelining, and OT extension. Our implementation is the first allowing entire circuits to be generated concurrently, and makes use of a modification of the XOR technique so that circuit generation is optimized for implementation on SIMD architectures of GPUs. In our best cases we generate about 75 million gates per second and we exceed the state of the art performance metrics on modern CPU systems by a factor of about 200, and GPU systems by about a factor of 2.3. While many recent works on garbled circuits exploit the embarrassingly parallel nature of many tasks that are part of a secure computation protocol, we show that there are still various forms and levels of parallelization that may yet improve the performance of these protocols. In particular, we highlight that implementations on the SIMD architecture of modern GPUs require significantly different approaches than the general purpose MIMD architecture of multi-core CPUs, which again differ from the needs of parallelizing on compute clusters. Additionally, modifications to the security models for many common protocols have large effects on reasonable parallel architectures for implementation.
GPU和CPU并行化的诚实但好奇的安全双方计算
最近的工作证明了安全两方计算的可行性和实际应用[5,9,15,23]。在这项工作中,我们提出了第一个图形处理单元(GPU)优化的实现,用于在诚实但好奇和1位泄漏的恶意模型中进行双方安全计算的优化Yao's乱码电路协议。我们实现了几乎所有现代协议的进步,如自由异或、流水线和OT扩展。我们的实现是第一个允许并发生成整个电路的实现,并利用对异或技术的修改,以便在gpu的SIMD架构上优化电路生成。在最好的情况下,我们每秒生成大约7500万个门,我们超过了现代CPU系统上最先进的性能指标大约200倍,GPU系统大约2.3倍。虽然最近许多关于乱码电路的工作利用了安全计算协议中许多任务令人尴尬的并行特性,但我们表明仍然存在各种形式和级别的并行化,这些并行化可能会提高这些协议的性能。我们特别强调,在现代gpu的SIMD体系结构上实现所需的方法与多核cpu的通用MIMD体系结构明显不同,这也不同于在计算集群上并行化的需求。此外,对许多通用协议的安全模型的修改对合理的并行体系结构的实现有很大的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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