Conditional Variational AutoEncoder based on Stochastic Attacks

Conditional Variational AutoEncoder based on Stochastic Attacks

Over the recent years, the cryptanalysis community leveraged the potential of research on Deep Learning to enhance attacks. In particular, several studies have recently highlighted the benefits of Deep Learning based Side-Channel Attacks (DLSCA) to target real-world cryptographic implementations. W...

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Bibliographic Details
Main Authors: Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
Format: Article
Language:English
Published: Ruhr-Universität Bochum 2023-03-01
Series:Transactions on Cryptographic Hardware and Embedded Systems
Subjects:
Side-Channel Attacks
Deep Learning
Generative Models
Discriminative Models
Stochastic Attacks
Variational AutoEncoder
Online Access:https://tches.iacr.org/index.php/TCHES/article/view/10286

Internet

https://tches.iacr.org/index.php/TCHES/article/view/10286

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