Hardware reverse engineering is a powerful and universal tool for both security engineers and adversaries. From a defensive perspective, it allows for detection of intellectual property infringements and hardware Trojans, while it simultaneously can be used for product piracy and malicious circuit manipulations. From a designer's perspective, it is crucial to have an estimate of the costs associated with reverse engineering, yet little is known about this, especially when dealing with obfuscated hardware. The contribution at hand provides new insights into this problem, based on algorithms with sound mathematical underpinnings. Our contributions are threefold: First, we present the graph similarity problem for automating hardware reverse engineering. To this end, we improve several state-of-the-art graph similarity heuristics with optimizations tailored to the hardware context. Second, we propose a novel algorithm based on multiresolutional spectral analysis of adjacency matrices. Third, in three extensively evaluated case studies, namely (1) gate-level netlist reverse engineering, (2) hardware Trojan detection, and (3) assessment of hardware obfuscation, we demonstrate the practical nature of graph similarity algorithms.

中文翻译：

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图相似性及其在硬件安全中的应用

硬件逆向工程对于安全工程师和攻击者来说都是一种强大且通用的工具。从防御的角度来看，它允许检测知识产权侵权和硬件木马，同时它可以用于产品盗版和恶意电路操作。从设计人员的角度来看，估算与逆向工程相关的成本至关重要，但对此知之甚少，尤其是在处理混淆硬件时。基于具有良好数学基础的算法，手头的贡献为这个问题提供了新的见解。我们的贡献有三方面：首先，我们提出了用于自动化硬件逆向工程的图相似性问题。为此，我们通过针对硬件上下文量身定制的优化改进了几种最先进的图相似性启发式方法。其次，我们提出了一种基于邻接矩阵多分辨率谱分析的新算法。第三，在三个广泛评估的案例研究中，即（1）门级网表逆向工程、（2）硬件木马检测和（3）硬件混淆评估，我们展示了图相似性算法的实用性。