Hardware Trojans classification for gate-level netlists using multi-layer neural networks

Kento Hasegawa; Masao Yanagisawa; Nozomu Togawa

doi:10.1109/IOLTS.2017.8046227

Hardware Trojans classification for gate-level netlists using multi-layer neural networks

Kento Hasegawa, Masao Yanagisawa, Nozomu Togawa

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

23 Citations (Scopus)

Abstract

Recently, due to the increase of outsourcing in IC design and manufacturing, it has been reported that malicious third-party IC vendors often insert hardware Trojans into their products. Especially in IC design step, it is strongly required to detect hardware Trojans because malicious third-party vendors can easily insert hardware Trojans in their products. In this paper, we propose a machine-learning-based hardware-Trojan detection method for gate-level netlists using multi-layer neural networks. First, we extract 11 Trojan-net feature values for each net in a netlist. After that, we classify the nets in an unknown netlist into a set of Trojan nets and that of normal nets using multi-layer neural networks. We obtained at most 100% true positive rate with our proposed method.

Original language	English
Title of host publication	2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	227-232
Number of pages	6
ISBN (Electronic)	9781538603512
DOIs	https://doi.org/10.1109/IOLTS.2017.8046227
Publication status	Published - 2017 Sep 19
Event	23rd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2017 - Thessaloniki, Greece Duration: 2017 Jul 3 → 2017 Jul 5

Other

Other	23rd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2017
Country	Greece
City	Thessaloniki
Period	17/7/3 → 17/7/5

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Keywords

Gate-level netlist
Hardware Trojan
Machine learning
Multi-layer
Neural network

ASJC Scopus subject areas

Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality
Computer Networks and Communications
Hardware and Architecture
Control and Systems Engineering

Cite this

Hasegawa, K., Yanagisawa, M., & Togawa, N. (2017). Hardware Trojans classification for gate-level netlists using multi-layer neural networks. In 2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017 (pp. 227-232). [8046227] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IOLTS.2017.8046227

Hardware Trojans classification for gate-level netlists using multi-layer neural networks. / Hasegawa, Kento; Yanagisawa, Masao ; Togawa, Nozomu.

2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 227-232 8046227.

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

Hasegawa, K, Yanagisawa, M & Togawa, N 2017, Hardware Trojans classification for gate-level netlists using multi-layer neural networks. in 2017 IEEE 23rd International Symposium on On-Line Testing and Robust System Design, IOLTS 2017., 8046227, Institute of Electrical and Electronics Engineers Inc., pp. 227-232, 23rd IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2017, Thessaloniki, Greece, 17/7/3. https://doi.org/10.1109/IOLTS.2017.8046227

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Access to Document

10.1109/IOLTS.2017.8046227