Deep learning-based rotational-XOR distinguishers for AND-RX block ciphers: evaluations on Simeck and Simon

DOI10.1007/978-3-031-53368-6_21MaRDI QIDQ6620063

David Gérault, Paolo Palmieri, Amirhossein Ebrahimi

Publication date: 16 October 2024

zbMATH Keywords

cryptanalysisdeep learningrotational-XOR cryptanalysisAND-RX ciphers

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Cryptography (94A60)

Cites Work

• Title not available (Why is that?)
• Rotational rebound attacks on reduced Skein
• Differential cryptanalysis of DES-like cryptosystems
• The \textsf{Simeck} family of lightweight block ciphers
• A deeper look at machine learning-based cryptanalysis
• Improving attacks on round-reduced Speck32/64 using deep learning
• Algebraic Cryptanalysis
• Rotational Cryptanalysis of ARX
• Automatic Search for Related-Key Differential Trails in SIMON-like Block Ciphers Based on MILP

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