Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs

Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs
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加速 GPU 上同态加密的有限域算法

DOI:
10.1109/mm.2023.3253052
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发表时间:
2023
期刊:
影响因子:
3.6
通讯作者:
Kaeli, David
Kaeli, David
中科院分区:
计算机科学3区
文献类型:
--
作者:
Livesay, Neal;Jonatan, Gilbert;Mora, Evelio;Shivdikar, Kaustubh;Agrawal, Rashmi;Joshi, Ajay;Abellán, José L.;Kim, John;Kaeli, David

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完全同态加密(FHE)是一种快速发展的技术,可以直接对加密数据进行计算,使其成为基于云的系统中引人注目的安全解决方案。此外,现代的FHE方案据信能够抵抗量子攻击。尽管FHE提供了前所未有的安全潜力,但当前的实现存在高得令人望而却步的延迟。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可并行化工作负载的目标。本文讨论了利用图形处理器加速多项式乘法运算的方法,以期达到实用化的目的。
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.
DOI: --
发表时间: 2017
期刊: IMA Conference on Cryptography and Coding
影响因子: --
作者:
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通讯作者: M. Scott
DOI: --
发表时间: 2020
期刊: IEEE International Symposium on Workload Characterization
影响因子: --
作者:
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通讯作者: Jung Ho Ahn