A Countermeasure to Power Analysis Attack by Arbitrarily Injecting Multiple Types of Noise

Tomoaki Ukezono, Yui Koyanagi
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Abstract

As the Internet of Things (IoT) society develops, cryptographic security becomes even more important. However, side channel security remains a vulnerability without a definitive solution. We focus on power analysis attacks that estimate internal information from processor power consumption which is one of side channels and propose lightweight countermeasures to reduce the area and delay overhead compared with conventional countermeasures. This paper proposes a novel very large-scale integrated circuit (VLSI) design method, arbitrary noise injector (ANI), that randomly selected noise into vulnerable circuit to achieve improvement in tamper resistance. In our evaluation, it has been confirmed that ANI achieves comparable tamper resistance to the conventional design method, WDDL, with a small area overhead of approximately 7%.
针对任意注入多种噪声的功率分析攻击的对策
随着物联网(IoT)社会的发展,加密安全变得更加重要。然而,侧信道安全仍然是一个没有明确解决方案的漏洞。我们重点研究了从作为侧信道之一的处理器功耗中估计内部信息的功耗分析攻击,并提出了轻量级的对抗措施,与传统的对抗措施相比,减少了面积和延迟开销。本文提出了一种新的超大规模集成电路(VLSI)设计方法——任意噪声注入器(ANI),将随机选择的噪声注入到脆弱电路中,以提高其抗篡改能力。在我们的评估中,已经证实ANI达到了与传统设计方法WDDL相当的抗篡改性,其面积开销约为7%。
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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