Novel Feature Selection for Non-destructive Detection of Hardware Trojans Using Hyperspectral Scanning
Author:
Funder
Office of Naval Research
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Building and Construction
Link
https://link.springer.com/content/pdf/10.1007/s41635-022-00127-7.pdf
Reference56 articles.
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2. Tehranipoor M, Koushanfar F (2010) A survey of hardware trojan taxonomy and detection. IEEE Des Test Comput 27(1):10–25. https://doi.org/10.1109/MDT.2010.7
3. Wang X, Tehranipoor M, Plusquellic J (2008) Detecting malicious inclusions in secure hardware: Challenges and solutions. In: 2008 IEEE International Workshop on Hardware-Oriented Security and Trust, pp 15–19. https://doi.org/10.1109/HST.2008.4559039
4. Xiao K, Forte D, Jin Y, Karri R, Bhunia S, Tehranipoor M (2016) Hardware trojans: Lessons learned after one decade of research. ACM Trans Des Autom Electron Syst 22(1). https://doi.org/10.1145/2906147
5. Botero UJ, Wilson R, Lu H, Rahman MT, Mallaiyan MA, Ganji F, Asadizanjani N, Tehranipoor MM, Woodard DL, Forte D (2021) Hardware trust and assurance through reverse engineering: A tutorial and outlook from image analysis and machine learning perspectives. J Emerg Technol Comput Syst 17(4)
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1. Hyperspectral Image Recovery via Reliability-Weighted Compressed Sensing for Hardware Trojan Detection;IEEE Access;2022
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