Hardware trojans classification based on controllability and observability in gate-level netlist

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Abstract

This paper presents a hardware Trojan classification method that performs a static analysis in gate-level netlist. Based on the controllability and observability characteristics extracted in a circuit, the nets are clustered into two groups with the k-means method. Then inter-cluster distance is measured and taken as the major feature for Trojan identification. By combined with three other features in terms of circuit scale statistic number, a complementary representation of Trojan circuits is constructed. Finally, a support vector machine classifier is trained to distinguish the Trojan circuits from genuine circuits. Experimental results on Trust-HUB benchmarks demonstrate that our method can achieve up to 100% true positive rate.

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Xie, X., Sun, Y., Chen, H., & Ding, Y. (2017). Hardware trojans classification based on controllability and observability in gate-level netlist. IEICE Electronics Express, 14(18). https://doi.org/10.1587/elex.14.20170682

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