A Full-Stack Solution for Side-Channel Security of Machine Learning Hardware.

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dc.contributor.advisorAydin Aysu, Chair
dc.contributor.advisorPaul Franzon, Member
dc.contributor.advisorJames Tuck, Member
dc.contributor.advisorRosario Cammarota, External
dc.contributor.advisorAlessandra Scafuro, Member
dc.contributor.authorDubey, Anuj
dc.date.accepted2023-05-26
dc.date.accessioned2024-06-11T12:30:26Z
dc.date.available2024-06-11T12:30:26Z
dc.date.defense2023-04-24
dc.date.embargo2024-06-09
dc.date.issued2023-04-24
dc.date.released2024-06-11
dc.date.reviewed2023-05-12
dc.date.submitted2023-05-08
dc.degree.disciplineComputer Engineering
dc.degree.leveldissertation
dc.degree.nameDoctor of Philosophy
dc.descriptionNorth Carolina State University Theses Electrical and Computer Engineering.
dc.formatPh.D. North Carolina State University, 2023.
dc.identifier.otherdeg33553
dc.identifier.urihttps://www.lib.ncsu.edu/resolver/1840.20/41902
dc.titleA Full-Stack Solution for Side-Channel Security of Machine Learning Hardware.
dcterms.extent1 online resource (xvi, 167 pages) : illustrations (some color)

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