Scalable Neural Cryptanalysis of Block Ciphers in Federated Attack Environments

This paper presents an extended investigation into deep learning-based cryptanalysis of block ciphers by introducing and evaluating a multi-server attack environment. Building upon our prior work in centralized settings, we explore the practicality and scalability of deploying such attacks across mu...

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Autors principals:	Ongee Jeong, Seonghwan Park, Inkyu Moon
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-01-01
Col·lecció:	Mathematics
Matèries:	block ciphers neural cryptanalysis distributed learning encryption emulation (EE) plaintext recovery (PR) data encryption standard (DES)
Accés en línia:	https://www.mdpi.com/2227-7390/14/2/373
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