Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits
1st ed. 2023. - Singapore: Springer Nature Singapore, Imprint: Springer, 2023
Online
Monographie, Elektronische Ressource
- 1 Online-Ressource (XIII, 84 p. 31 illus., 18 illus. in color)
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Titel: |
Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits
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Verantwortlichkeitsangabe: | by Pranesh Santikellur, Rajat Subhra Chakraborty |
Autor/in / Beteiligte Person: | Santikellur, Pranesh ; Chakraborty, Rajat Subhra |
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Ausgabe: | 1st ed. 2023 |
Veröffentlichung: | Singapore: Springer Nature Singapore, Imprint: Springer, 2023 |
Medientyp: | Monographie |
Datenträgertyp: | Elektronische Ressource |
Umfang: | 1 Online-Ressource (XIII, 84 p. 31 illus., 18 illus. in color) |
ISBN: | 9789811940170 |
DOI: | 10.1007/978-981-19-4017-0 |
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