Since 2007, the use of side-channel measurements for detecting Hardware Trojan (HT) has been extensively studied. However, the majority of works either rely on a golden chip, or they rely on methods that are not robust against subtle acceptable changes that would occur over the life-cycle of an integrated circuit (IC). In this paper, we propose using a brain-inspired architecture called Hierarchical Temporal Memory (HTM) for HT detection. Similar to the human brain, our proposed solution is resilient against natural changes that might happen in the side-channel measurements while being able to accurately detect abnormal behavior of the chip when the HT gets triggered. We use a self-referencing method for HT detection, which eliminates the need for the golden chip. The effectiveness of our approach is evaluated using TrustHub benchmarks, which shows 92.20% detection accuracy on average.

中文翻译：

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受大脑启发的金芯片免费硬件特洛伊木马检测

自2007年以来，已经广泛研究了使用边信道测量来检测硬件特洛伊木马（HT）。但是，大多数工作要么依赖于金芯片，要么依赖于对在集成电路（IC）的整个生命周期中可能发生的微妙的可接受变化没有鲁棒性的方法。在本文中，我们建议使用称为“时间记忆”（Herarchical Temporal Memory，HTM）的大脑启发性架构进行HT检测。与人的大脑类似，我们提出的解决方案可以抵抗自然边通道测量中可能发生的变化，同时能够在触发HT时准确检测芯片的异常行为。我们使用自参考方法进行HT检测，从而无需使用金芯片。我们的方法的有效性使用TrustHub基准进行了评估，该基准显示出平均92.20％的检测准确性。