GPU上用于同态加密的加速有限域算法

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

IEEE Micro Pub Date : 2023-09-01 DOI:10.1109/MM.2023.3253052

Neal Livesay, Gilbert Jonatan, Evelio Mora, Kaustubh Shivdikar, R. Agrawal, Ajay Joshi, José L. Abellán, John Kim, D. Kaeli

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引用次数: 2

摘要

完全同态加密(FHE)是一种快速发展的技术，可以直接在加密数据上进行计算，使其成为基于云的系统中引人注目的安全解决方案。此外，现代FHE方案被认为能够抵抗量子攻击。尽管FHE提供了前所未有的安全潜力，但目前的实现存在过高的延迟。有限域算术运算，特别是高次多项式的乘法运算，是关键的计算瓶颈。现代gpu提供的并行处理能力使它们成为这些高度并行工作负载的有力候选。在本文中，我们讨论了用gpu加速多项式乘法的方法，目的是使FHE实用。

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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Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs

Fully homomorphic encryption (FHE) is a rapidly developing technology that enables computation directly on encrypted data, making it a compelling solution for security in cloud-based systems. In addition, modern FHE schemes are believed to be resistant to quantum attacks. Although FHE offers unprecedented potential for security, current implementations suffer from prohibitively high latency. Finite field arithmetic operations, particularly the multiplication of high-degree polynomials, are key computational bottlenecks. The parallel processing capabilities provided by modern GPUs make them compelling candidates to target these highly parallelizable workloads. In this article, we discuss methods to accelerate polynomial multiplication with GPUs, with the goal of making FHE practical.

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来源期刊

IEEE Micro 工程技术-计算机：软件工程

CiteScore

7.50

自引率

0.00%

发文量

164

审稿时长

>12 weeks

期刊介绍： IEEE Micro addresses users and designers of microprocessors and microprocessor systems, including managers, engineers, consultants, educators, and students involved with computers and peripherals, components and subassemblies, communications, instrumentation and control equipment, and guidance systems. Contributions should relate to the design, performance, or application of microprocessors and microcomputers. Tutorials, review papers, and discussions are also welcome. Sample topic areas include architecture, communications, data acquisition, control, hardware and software design/implementation, algorithms (including program listings), digital signal processing, microprocessor support hardware, operating systems, computer aided design, languages, application software, and development systems.