Detection Method of Hardware Trojan Based on Attention Mechanism and Residual-Dense-Block under the Markov Transition Field-Reference-Cited by-同舟云学术

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Detection Method of Hardware Trojan Based on Attention Mechanism and Residual-Dense-Block under the Markov Transition Field

Published:2023-12 Issue:5-6 Volume:39 Page:621-629
ISSN:0923-8174
Container-title:Journal of Electronic Testing
language:en
Short-container-title:J Electron Test

Author:

Chen Shouhong,Wang Tao,Huang Zhentao,Hou Xingna

Funder

the National Natural Science Foundation of China

the Guangxi Natural Science Foundation

the Basic Ability Enhancement Program for Young and Middle-aged Teachers of Guangxi

Innovation Project of GUET Graduate Education

Guangxi Key Laboratory of Automation Test and Instrumentation

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Link

https://link.springer.com/content/pdf/10.1007/s10836-023-06090-7.pdf

Reference41 articles.

1. Agrawal D, Baktir S, Karakoyunlu D, Rohatgi P, Sunar B (2007) Trojan Detection using IC Fingerprinting. Proc.2007 IEEE Symposium on Security and Privacy (SP ’07). Berkeley, CA, USA, pp 296–310

2. Bao C, Forte D, Srivastava A (2014) On application of one-class SVM to reverse engineering-based hardware Trojan detection. Proc. Fifteenth International Symposium on Quality Electronic Design. Santa Clara, CA, USA, pp 47–54

3. Chen S, Wang T, Huang Z, Hou X (2023) Detection method of Golden Chip-Free Hardware Trojan based on the combination of ResNeXt structure and attention mechanism. Comput Secur 134:103428

4. Dubeuf J, Hély D, Karri R (2013) Run-time detection of hardware Trojans: The processor protection unit. Proc.2013 18th IEEE European Test Symposium (ETS). Avignon, France, pp 1–6

5. Faezi S, Yasaei R, Al Faruque MA (2021) HTnet: Transfer learning for golden chip-free hardware trojan detection. Proc.2021 Design, Automation & Test in Europe Conference & Exhibition (DATE). Grenoble, France, pp 1484–1489

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