Performance Evaluation of SHA-2 Standard vs. SHA-3 Finalists on Two Freescale Platforms

Pal-Stefan Murvay, B. Groza
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引用次数: 3

Abstract

Embedded devices are ubiquitously involved in a large variety of security applications which heavily rely on the computation of hash functions. Roughly, two alternatives for speeding up computations co-exist in these resource constrained devices: parallel processing and hardware acceleration. Needles to say, multi-core devices are clearly the next step in embedded systems due to clear technological limitations on single processor frequency. Hardware accelerators are long known to be a cheaper approach for costly cryptographic functions. The authors analysis is focused on the five SHA-3 finalists which are also contrasted to the previous SHA-2 standard and to the widespread MD5. On the hardware side, the authors deploy their implementations on two platforms from Freescale: a S12X core equipped with an XGATE coprocessor and a Kinetis K60 core equipped with a crypto co-processor. These platforms differ significantly in terms of computational power, the first is based on a 16-bit Freescale proprietary architecture while the former relies on a more recent 32-bit Cortex core. The authors' experimental results show mixed performances between the old standard and the new candidates. Some of the new candidates clearly outperform the old standard in terms of both computational speed and memory requirements while others do not. Bottom line, on the 16 bit platform BLAKE and Grostl are the top performers while on the 32-bit platform Keccak, Blake and Skein give the best results.
两种飞思卡尔平台上SHA-2标准与SHA-3最终入选者的性能评估
嵌入式设备在大量依赖于哈希函数计算的安全应用中无处不在。粗略地说,在这些资源受限的设备中存在两种加速计算的替代方案:并行处理和硬件加速。可以说,由于单处理器频率的技术限制,多核设备显然是嵌入式系统的下一步。对于昂贵的加密功能,硬件加速器一直被认为是一种更便宜的方法。作者的分析集中在五个SHA-3最终入围者上,它们也与之前的SHA-2标准和广泛使用的MD5进行了对比。在硬件方面,作者在飞思卡尔的两个平台上部署了他们的实现:一个配备XGATE协处理器的S12X核心和一个配备加密协处理器的Kinetis K60核心。这些平台在计算能力方面有很大的不同,第一个平台基于16位飞思卡尔的专有架构,而前者依赖于最近的32位Cortex核心。作者的实验结果表明,旧标准和新候选标准的性能参差不齐。在计算速度和内存需求方面,一些新的候选标准明显优于旧标准,而另一些则没有。最重要的是,在16位平台上,BLAKE和Grostl的表现最好,而在32位平台上,Keccak、BLAKE和Skein的表现最好。
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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