Side-Channel Attack Counteraction via Machine Learning-Targeted Power Compensation for Post-Silicon HW Security Patching

Please use this identifier to cite or link to this item: https://doi.org/10.1109/ISSCC42614.2022.9731755

Title:	Side-Channel Attack Counteraction via Machine Learning-Targeted Power Compensation for Post-Silicon HW Security Patching
Authors:	Qiang Fang LIN LONGYANG YAO ZU WONG Hui Zhang Alioto,Massimo Bruno
Issue Date:	17-Mar-2022
Publisher:	IEEE
Citation:	Qiang Fang, LIN LONGYANG, YAO ZU WONG, Hui Zhang, Alioto,Massimo Bruno (2022-03-17). Side-Channel Attack Counteraction via Machine Learning-Targeted Power Compensation for Post-Silicon HW Security Patching. 2022 IEEE International Solid- State Circuits Conference (ISSCC). ScholarBank@NUS Repository. https://doi.org/10.1109/ISSCC42614.2022.9731755
Related Dataset(s):	10.1109/ISSCC42614.2022.9731755
Source Title:	2022 IEEE International Solid- State Circuits Conference (ISSCC)
URI:	https://scholarbank.nus.edu.sg/handle/10635/225716
DOI:	10.1109/ISSCC42614.2022.9731755
Appears in Collections:	Staff Publications Elements Students Publications

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