%X Hardware Trojan refers to a malicious modification of an integrated circuit (IC). To eliminate the complications arising from designing an IC which includes a Trojan, it is suggested to apply Trojan detection as early as at register-transfer level (RTL). In this paper, we propose a hardware Trojan detection framework which consists of both RTL and gate-level classification using machine learning approaches to detect hardware Trojan inserted at RTL. In the experiment, all Trojan benchmarks were successfully identified without false positive detection on non-Trojan benchmark. © 2019 IEEE.
%J Proceedings of the Asian Test Symposium
%O cited By 6; Conference of 28th IEEE Asian Test Symposium, ATS 2019 ; Conference Date: 10 December 2019 Through 13 December 2019; Conference Code:156685
%D 2019
%L scholars11018
%T Machine-Learning-Based Multiple Abstraction-Level Detection of Hardware Trojan Inserted at Register-Transfer Level
%I IEEE Computer Society
%A H.S. Choo
%A C.Y. Ooi
%A M. Inoue
%A N. Ismail
%A M. Moghbel
%A S. Baskara Dass
%A C.H. Kok
%A F.A. Hussin
%V 2019-D
%K Integrated circuits; Learning systems; Machine learning; Malware, Abstraction level; False positive detection; Gate levels; Hardware Trojan detection; Machine learning approaches; Register transfer level; Trojan detections; Trojans, Hardware security
%R 10.1109/ATS47505.2019.00018
%P 98