On using control signals for word-level identification in a gate-level netlist
On using control signals for word-level identification in a gate-level netlist
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关于在门级网表中使用控制信号进行字级识别
DOI：
10.1145/2744769.2744878
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
A. Davoodi
中科院分区：
文献类型：
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作者：
Edward Tashjian;A. Davoodi
这项工作解决了对门级网表进行逆向工程的问题，以便识别与字相对应的电线组。它是查找高级模块并在存在硬件木马的情况下分析其正确功能的主要步骤。我们的核心思想是寻找并利用控制信号来更有效地识别单词。具体来说，现代设计提供了充足的机会，因为它们包含大量由 CAD 工具自动插入的控制信号。但寻找控制信号本身就是一个尚未解决的挑战。我们提出了一种识别单词的过程，其核心是通过利用部分结构相似性来查找和利用相关控制信号的一小部分。在我们的实验中，我们使用许多基准以已识别的单词作为参考案例，以高精度显示大量已识别的单词，从而证明了我们的程序的有效性。
This work tackles the problem of reverse engineering a gate-level netlist in order to identify groups of wires corresponding to words. It serves as the major step to find high-level modules and analyze their correct functionality in the presence of Hardware Trojans. Our core idea is to find and utilize control signals to more effectively identify words. Specifically, modern designs provide ample opportunities because they contain numerous control signals which are automatically inserted by the CAD tools. But finding control signals is itself an unresolved challenge. We propose a procedure to identify words which at its core finds and utilizes a small subset of relevant control signals by exploiting partial structural similarity. In our experiments, we show the effectiveness of our procedure by showing a high number of identified words with high accuracy using many benchmarks with already-identified words as the reference case.