Deep learning for side-channel analysis and introduction to ASCAD database

Recent works have demonstrated that deep learning algorithms were efficient to conduct security evaluations of embedded systems and had many advantages compared to the other methods. Unfortunately, their hyper-parametrization has often been kept secret by the authors who only discussed on the main d...

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Veröffentlicht in:	Journal of cryptographic engineering Jg. 10; H. 2; S. 163 - 188
Hauptverfasser:	Benadjila, Ryad, Prouff, Emmanuel, Strullu, Rémi, Cagli, Eleonora, Dumas, Cécile
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020 Springer Nature B.V Springer
Schlagworte:	Algorithms Artificial neural networks Benchmarks Circuits and Systems Communications Engineering Computer Communication Networks Computer Science Context Cryptography and Security Cryptology Data Structures and Information Theory Deep learning Electromagnetic measurement Embedded systems Machine learning Networks Object recognition Operating Systems Parameterization Questions Regular Paper Reproducibility Systems analysis Deep learning Side-channel analysis Machine learning
ISSN:	2190-8508, 2190-8516
Online-Zugang:	Volltext
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