Optimizing Hardware Resource Utilization for Accelerating the NTRU-KEM Algorithm

IF 2.6 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers Pub Date : 2023-12-13 DOI:10.3390/computers12120259
Yongseok Lee, Jonghee Youn, Kevin Nam, Hyunyoung Oh, Y. Paek
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Abstract

This paper focuses on enhancing the performance of the Nth-degree truncated-polynomial ring units key encapsulation mechanism (NTRU-KEM) algorithm, which ensures post-quantum resistance in the field of key establishment cryptography. The NTRU-KEM, while robust, suffers from increased storage and computational demands compared to classical cryptography, leading to significant memory and performance overheads. In environments with limited resources, the negative impacts of these overheads are more noticeable, leading researchers to investigate ways to speed up processes while also ensuring they are efficient in terms of area utilization. To address this, our research carefully examines the detailed functions of the NTRU-KEM algorithm, adopting a software/hardware co-design approach. This approach allows for customized computation, adapting to the varying requirements of operational timings and iterations. The key contribution is the development of a novel hardware acceleration technique focused on optimizing bus utilization. This technique enables parallel processing of multiple sub-functions, enhancing the overall efficiency of the system. Furthermore, we introduce a unique integrated register array that significantly reduces the spatial footprint of the design by merging multiple registers within the accelerator. In experiments conducted, the results of our work were found to be remarkable, with a time-area efficiency achieved that surpasses previous work by an average of 25.37 times. This achievement underscores the effectiveness of our optimization in accelerating the NTRU-KEM algorithm.
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优化硬件资源利用以加速 NTRU-KEM 算法
本文的重点是提高 Nth 度截断多项式环单元密钥封装机制(NTRU-KEM)算法的性能,该算法可确保密钥建立加密领域的后量子抗性。与经典密码学相比,NTRU-KEM 虽然稳健,但存储和计算需求增加,导致内存和性能开销巨大。在资源有限的环境中,这些开销带来的负面影响更加明显,因此研究人员开始研究如何在加快处理速度的同时确保有效利用空间。为此,我们的研究采用软硬件协同设计方法,仔细研究了 NTRU-KEM 算法的详细功能。这种方法允许进行定制计算,以适应操作时序和迭代的不同要求。其主要贡献在于开发了一种新型硬件加速技术,重点是优化总线利用率。该技术实现了多个子功能的并行处理,提高了系统的整体效率。此外,我们还引入了一种独特的集成寄存器阵列,通过合并加速器内的多个寄存器,大大减少了设计的空间占用。在实验中,我们的工作取得了显著的成果,所实现的时间-面积效率比以前的工作平均高出 25.37 倍。这一成果凸显了我们的优化在加速 NTRU-KEM 算法方面的有效性。
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来源期刊
Computers
Computers COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
5.40
自引率
3.60%
发文量
153
审稿时长
11 weeks
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