Implementing Region-Based Segmentation for Hardware Trojan Detection in FPGAs Cell-Level Netlist-Reference-Cited by-同舟云学术

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Implementing Region-Based Segmentation for Hardware Trojan Detection in FPGAs Cell-Level Netlist

Published:2023-11-01 Issue:11 Volume:E106.D Page:1926-1929
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

TIEMPO Ann Jelyn¹,JEONG Yong-Jin¹

Affiliation:

1. Dept. of Electronics and Communications Engineering, Kwangwoon University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E106.D/11/E106.D_2023EDL8036/_pdf

Reference14 articles.

1. [1] H. Li, Q. Liu, and J. Zhang, “A survey of hardware Trojan threat and defense,” Integr. VLSI J., vol.55, pp.426-437, 2016. 10.1016/j.vlsi.2016.01.004 10.1016/j.vlsi.2016.01.004

2. [2] K.G. Liakos, G.K. Georgakilas, S. Moustakidis, N. Sklavos, and F.C. Plessas, “Conventional and machine learning approaches as countermeasures against hardware trojan attacks,” Microprocess Microsys, vol.79, p.103295, 2020. 10.1016/j.micpro.2020.103295

3. [3] Z. Huang, Q. Wang, Y. Chen, and X. Jiang, “A Survey on Machine Learning Against Hardware Trojan Attacks: Recent Advances and Challenges,” IEEE Access, vol.8, pp.10796-10826, 2020, doi:10.1109/ACCESS.2020.2965016. 10.1109/access.2020.2965016

4. [4] M. Xue, C. Gu, W. Liu, S. Yu, and M. O'Neill, “Ten years of hardware Trojans: A survey from the attacker's perspective,” IET Comput. Digit. Techn., vol.14, no.6, pp.231-246, 2020. 10.1049/iet-cdt.2020.0041

5. [5] C. Marchand and J. Francq, “Low-level implementation and side-channel detection of stealthy hardware Trojans on field programmable gate arrays,” IET Comput. Digit. Tech., vol.8, no.6, pp.246-255, 2014. 10.1049/iet-cdt.2014.0034

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