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Blind Cartography for Side Channel Attacks: Cross-Correlation Cartography

机译:侧通道攻击的盲图:互相关图

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Side channel and fault injection attacks are major threats to cryptographic applications of embedded systems. Best performances for these attacks are achieved by focusing sensors or injectors on the sensible parts of the application, by means of dedicated methods to localise them. Few methods have been proposed in the past, and all of them aim at pinpointing the cryptoprocessor. However it could be interesting to exploit the activity of other parts of the application, in order to increase the attack's efficiency or to bypass its countermeasures. In this paper, we present a localisation method based on cross-correlation, which issues a list of areas of interest within the attacked device. It realizes an exhaustive analysis, since it may localise any module of the device, and not only those which perform cryptographic operations. Moreover, it also does not require a preliminary knowledge about the implementation, whereas some previous cartography methods require that the attacker could choose the cryptoprocessor inputs, which is not always possible. The method is experimentally validated using observations of the electromagnetic near field distribution over a Xilinx Virtex 5 FPGA. The matching between areas of interest and the application layout in the FPGA floorplan is confirmed by correlation analysis.
机译:侧通道和故障注入攻击是对嵌入式系统密码应用程序的主要威胁。这些攻击的最佳性能是通过将传感器或注入器聚焦在应用程序的敏感部分上,并通过专用的方法对其进行定位的。过去很少提出方法,所有这些方法都旨在查明密码处理器。但是,利用应用程序其他部分的活动来提高攻击效率或绕过其对策可能会很有趣。在本文中,我们提出了一种基于互相关的定位方法,该方法可在受攻击设备内发布感兴趣区域的列表。它实现了详尽的分析,因为它可以定位设备的任何模块,而不仅限于执行加密操作的模块。此外,它也不需要有关实现的初步知识,而某些先前的制图方法要求攻击者可以选择加密处理器输入,而这并非总是可能的。通过在Xilinx Virtex 5 FPGA上观察电磁近场分布,对该方法进行了实验验证。通过相关分析,可以确定感兴趣的区域与FPGA布局图中的应用布局之间的匹配。

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