HTV: Measuring Circuit Vulnerability to Hardware Trojan Insertion Based on Node Co-activation Analysis

Hardware Trojans (HTs) pose a significant threat to the security of integrated circuits(ICs). Measuring the vulnerability of ICs to HT insertions is crucial for enhancing design security, thereby mitigating potential security risks. This paper proposes a novel vulnerability measurement method for ICs against HT insertions based on node co-activation analysis. The method first transforms the circuit structure into a graph representation, where nodes represent circuit interconnections, and edges represent circuit components, using graph learning (GL) techniques. Next, it calculates the logical probability distribution and logic flip probability for each circuit node using simulation methods. By combining an adaptive threshold filtering strategy, the method identifies suspicious nodes in the circuit using simulation methods combined with an adaptive threshold screening strategy to identify suspicious nodes in circuits. Subsequently, it computes the joint probabilities of pairs of suspicious nodes that simultaneously exhibit rare logic values based on simulation results. Finally, the vulnerability of the circuit to HT insertions is quantified by evaluating the co-activation between pairs of suspicious nodes. Experimental results demonstrate the effectiveness, efficiency, and generalization capability of the proposed method.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/trustcom63139.2024.00219
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
0.00

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article

HTV: Measuring Circuit Vulnerability to Hardware Trojan Insertion Based on Node Co-activation Analysis

Zhanhui Shi, Aizhu Liu, Jie Xiao, Sanbao Chai et al.
Physical Unclonable Functions (PUFs) and Hardware Security
article

HTV: Measuring Circuit Vulnerability to Hardware Trojan Insertion Based on Node Co-activation Analysis

Zhanhui Shi, Aizhu Liu, Jie Xiao, Sanbao Chai, Yuhe Gao, Yuhao Huang
article en

Abstract

Hardware Trojans (HTs) pose a significant threat to the security of integrated circuits(ICs). Measuring the vulnerability of ICs to HT insertions is crucial for enhancing design security, thereby mitigating potential security risks. This paper proposes a novel vulnerability measurement method for ICs against HT insertions based on node co-activation analysis. The method first transforms the circuit structure into a graph representation, where nodes represent circuit interconnections, and edges represent circuit components, using graph learning (GL) techniques. Next, it calculates the logical probability distribution and logic flip probability for each circuit node using simulation methods. By combining an adaptive threshold filtering strategy, the method identifies suspicious nodes in the circuit using simulation methods combined with an adaptive threshold screening strategy to identify suspicious nodes in circuits. Subsequently, it computes the joint probabilities of pairs of suspicious nodes that simultaneously exhibit rare logic values based on simulation results. Finally, the vulnerability of the circuit to HT insertions is quantified by evaluating the co-activation between pairs of suspicious nodes. Experimental results demonstrate the effectiveness, efficiency, and generalization capability of the proposed method.

Zhejiang University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 68%
Physical Unclonable Functions (PUFs) and Hardware Security
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