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An Improved Machine-Learning Model for the Identification and Classification of Memory-Based PUF Responses

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dc.contributor.authorMexis, Nico
dc.contributor.authorAnagnostopoulos, Nikolaos Athanasios
dc.contributor.authorArul, Tolga
dc.contributor.authorKavun, Elif Bilge
dc.contributor.authorKatzenbeisser, Stefan
dc.contributor.editorKrämer, Juliane
dc.contributor.editorAulbach, Thomas
dc.contributor.editorNüsken, Michael
dc.date.accessioned2024-04-16T12:38:34Z
dc.date.available2024-04-16T12:38:34Z
dc.date.issued2023
dc.identifier.doi10.18420/cdm-2023-35-03
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43932
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V. / FG KRYPTO
dc.relation.ispartofcrypto day matters 34
dc.relation.ispartofseriescrypto day matters
dc.titleAn Improved Machine-Learning Model for the Identification and Classification of Memory-Based PUF Responsesen
dc.typeText/Abstract
gi.conference.date25.-26. Juni 2023
gi.conference.locationRegensburg
gi.conference.sessiontitleKurzbeitrag

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Krypto-Tag 35 (2023)