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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Hlavní autoři:	Ongee Jeong, Seonghwan Park, Inkyu Moon
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2026-01-01
Edice:	Mathematics
Témata:	block ciphers neural cryptanalysis distributed learning encryption emulation (EE) plaintext recovery (PR) data encryption standard (DES)
On-line přístup:	https://www.mdpi.com/2227-7390/14/2/373
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