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Hardware Trojans (HTs) have become a major threat for the integrated circuit industry and supply chain and have motivated numerous developments of HT detection schemes. Although the side-channel HT detection approach is among the most promising solutions, most of the previous methods require a trusted golden chip reference. Furthermore, detection accuracy is often influenced by environmental noise and process variations. In this article, a novel electromagnetic (EM) side-channel fingerprinting-based HT detection method is proposed. Different from previous methods, the proposed solution eliminates the requirement of a trusted golden fabricated chip. Rather, only the genuine RTL code is required to generate the EM signatures as references. A factor analysis method is utilized to extract the spectral features of the HT trigger’s EM radiation, and then a k -means clustering method is applied for HT detection. Experimentation on two selected sets of Trust-Hub benchmarks has been performed on FPGA platforms, and the results show that the proposed framework can detect all dormant HTs with a high confidence level.
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He et al. (2020) studied this question.
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