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

DC Field	Value
dc.title	Side-Channel Attack Counteraction via Machine Learning-Targeted Power Compensation for Post-Silicon HW Security Patching
dc.contributor.author	Qiang Fang
dc.contributor.author	LIN LONGYANG
dc.contributor.author	YAO ZU WONG
dc.contributor.author	Hui Zhang
dc.contributor.author	Alioto,Massimo Bruno
dc.date.accessioned	2022-05-18T09:18:37Z
dc.date.available	2022-05-18T09:18:37Z
dc.date.issued	2022-03-17
dc.identifier.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
dc.identifier.uri	https://scholarbank.nus.edu.sg/handle/10635/225716
dc.description.uri	https://ieeexplore-ieee-org.libproxy1.nus.edu.sg/abstract/document/9731755
dc.language.iso	en
dc.publisher	IEEE
dc.type	Conference Paper
dc.contributor.department	ELECTRICAL AND COMPUTER ENGINEERING
dc.description.doi	10.1109/ISSCC42614.2022.9731755
dc.description.sourcetitle	2022 IEEE International Solid- State Circuits Conference (ISSCC)
dc.published.state	Published
dc.grant.id	“SOCure” grant NRF2018NCR-NCR002-0001
dc.grant.fundingagency	Singapore National Research Foundation
dc.relation.dataset	10.1109/ISSCC42614.2022.9731755
Appears in Collections:	Staff Publications Elements Students Publications

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