TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection

Hazem Lashen; Lilas Alrahis; Johann Knechtel; Ozgur Sinanoglu

doi:10.1109/ISCAS46773.2023.10181403

TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection

Hazem Lashen, Lilas Alrahis, Johann Knechtel, Ozgur Sinanoglu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We propose TrojanSAINT, a graph neural network (GNN)-based hardware Trojan (HT) detection scheme working at the gate level. Unlike prior GNN-based art, TrojanSAINT enables both pre-/post-silicon HT detection. TrojanSAINT leverages a sampling-based GNN framework to detect and also localize HTs. For practical validation, TrojanSAINT achieves on average (oa) 78% true positive rate (TPR) and 85% true negative rate (TNR), respectively, on various TrustHub HT benchmarks. For best-case validation, TrojanSAINT even achieves 98% TPR and 96% TNR oa. TrojanSAINT outperforms related prior works and baseline classifiers. We release our source codes and result artifacts.

Original language	English (US)
Title of host publication	ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665451093
DOIs	https://doi.org/10.1109/ISCAS46773.2023.10181403
State	Published - 2023
Event	56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 - Monterey, United States Duration: May 21 2023 → May 25 2023

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2023-May
ISSN (Print)	0271-4310

Conference

Conference	56th IEEE International Symposium on Circuits and Systems, ISCAS 2023
Country/Territory	United States
City	Monterey
Period	5/21/23 → 5/25/23

Keywords

GNNs
Hardware Security
Trojan Detection

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ISCAS46773.2023.10181403

Cite this

Lashen, H., Alrahis, L., Knechtel, J., & Sinanoglu, O. (2023). TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection. In ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2023-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS46773.2023.10181403

TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection. / Lashen, Hazem; Alrahis, Lilas; Knechtel, Johann et al.
ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2023-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lashen, H, Alrahis, L, Knechtel, J & Sinanoglu, O 2023, TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection. in ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2023-May, Institute of Electrical and Electronics Engineers Inc., 56th IEEE International Symposium on Circuits and Systems, ISCAS 2023, Monterey, United States, 5/21/23. https://doi.org/10.1109/ISCAS46773.2023.10181403

Lashen H, Alrahis L, Knechtel J, Sinanoglu O. TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection. In ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings - IEEE International Symposium on Circuits and Systems). doi: 10.1109/ISCAS46773.2023.10181403

Lashen, Hazem ; Alrahis, Lilas ; Knechtel, Johann et al. / TrojanSAINT : Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection. ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - IEEE International Symposium on Circuits and Systems).

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title = "TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection",

abstract = "We propose TrojanSAINT, a graph neural network (GNN)-based hardware Trojan (HT) detection scheme working at the gate level. Unlike prior GNN-based art, TrojanSAINT enables both pre-/post-silicon HT detection. TrojanSAINT leverages a sampling-based GNN framework to detect and also localize HTs. For practical validation, TrojanSAINT achieves on average (oa) 78% true positive rate (TPR) and 85% true negative rate (TNR), respectively, on various TrustHub HT benchmarks. For best-case validation, TrojanSAINT even achieves 98% TPR and 96% TNR oa. TrojanSAINT outperforms related prior works and baseline classifiers. We release our source codes and result artifacts.",

keywords = "GNNs, Hardware Security, Trojan Detection",

author = "Hazem Lashen and Lilas Alrahis and Johann Knechtel and Ozgur Sinanoglu",

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AB - We propose TrojanSAINT, a graph neural network (GNN)-based hardware Trojan (HT) detection scheme working at the gate level. Unlike prior GNN-based art, TrojanSAINT enables both pre-/post-silicon HT detection. TrojanSAINT leverages a sampling-based GNN framework to detect and also localize HTs. For practical validation, TrojanSAINT achieves on average (oa) 78% true positive rate (TPR) and 85% true negative rate (TNR), respectively, on various TrustHub HT benchmarks. For best-case validation, TrojanSAINT even achieves 98% TPR and 96% TNR oa. TrojanSAINT outperforms related prior works and baseline classifiers. We release our source codes and result artifacts.

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TrojanSAINT: Gate-Level Netlist Sampling-Based Inductive Learning for Hardware Trojan Detection

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this