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Structural and SCOAP features based approach for hardware Trojan detection using SHAP and Light Gradient Boosting model
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  • Richa Sharma ,
  • G.K. Sharma ,
  • Manisha Pattanaik ,
  • VSS Prashant
Richa Sharma

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G.K. Sharma
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Manisha Pattanaik
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VSS Prashant
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Hardware Trojan (HT) is the most critical threat due to outsourcing of Integrated circuit designing phases. Therefore, a new technique is proposed that utilizes structural and SCOAP features to detect HT from the gate-level netlist using Light Gradient Boosting (Light GBM). Further, a model agnostic Shapley additive explanations (SHAP) is employed to identify each feature global and local impact on model prediction. Moreover, a quartile-based feature selection method is proposed, which uses SHAP to identify the optimal feature set by keeping low retraining rounds. Experimental results show that the proposed technique accurately detects always-on-Trojans and HT nets from Trust-Hub, DeTrust, and DeTest benchmarks.
Aug 2023Published in Journal of Electronic Testing volume 39 issue 4 on pages 465-485. 10.1007/s10836-023-06080-9