Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
Meet-in-the-Filter and Dynamic Counting with Applications to Speck
BIRYUKOV, Alexei; CARDOSO DOS SANTOS, Luan; TEH, Je Sen et al.
2023In Tibouchi, Mehdi; Wang, Xiaofeng (Eds.) Applied Cryptography and Network Security, 21st International Conference, ACNS 2023, Kyoto, Japan, June 19–22, 2023, Proceedings, Part I
Peer reviewed
 

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Mots-clés :
Symmetric-key; Differential cryptanalysis; ARX; Speck
Résumé :
[en] We propose a new cryptanalytic tool for differential cryptanalysis, called meet-in-the-filter (MiF). It is suitable for ciphers with a slow or incomplete diffusion layer such as the ones based on Addition-Rotation-XOR (ARX). The main idea of the MiF technique is to stop the difference propagation earlier in the cipher, allowing to use differentials with higher probability. This comes at the expense of a deeper analysis phase in the bottom rounds possible due to the slow diffusion of the target cipher. The MiF technique uses a meet-in-the-middle matching to construct differential trails connecting the differential’s output and the ciphertext difference. The proposed trails are used in the key recovery procedure, reducing time complexity and allowing flexible time-data trade-offs. In addition, we show how to combine MiF with a dynamic counting technique for key recovery. We illustrate MiF in practice by reporting improved attacks on the ARXbased family of block ciphers Speck. We improve the time complexities of the best known attacks up to 15 rounds of Speck32 and 20 rounds of Speck64/128. Notably, our new attack on 11 rounds of Speck32 has practical analysis and data complexities of 224.66 and 226.70 respectively, and was experimentally verified, recovering the master key in a matter of seconds. It significantly improves the previous deep learning-based attack by Gohr from CRYPTO 2019, which has time complexity 238. As an important milestone, our conventional cryptanalysis method sets a new high benchmark to beat for cryptanalysis relying on machine learning.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
BIRYUKOV, Alexei ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
CARDOSO DOS SANTOS, Luan ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
TEH, Je Sen ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Cryptolux ; Universiti Sains Malaysia
UDOVENKO, Aleksei  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Cryptolux
Velichkov, Vesselin;  University of Edinburgh
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Meet-in-the-Filter and Dynamic Counting with Applications to Speck
Date de publication/diffusion :
2023
Nom de la manifestation :
21st International Conference on Applied Cryptography and Network Security
Lieu de la manifestation :
Kyoto, Japon
Date de la manifestation :
from 19-06-2023 to 22-06-2023
Manifestation à portée :
International
Titre de l'ouvrage principal :
Applied Cryptography and Network Security, 21st International Conference, ACNS 2023, Kyoto, Japan, June 19–22, 2023, Proceedings, Part I
Editeur scientifique :
Tibouchi, Mehdi
Wang, Xiaofeng
Maison d'édition :
Springer
Pagination :
149-177
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
URL complémentaire :
Projet FnR :
FNR13641232 - Analysis And Protection Of Lightweight Cryptographic Algorithms, 2019 (01/01/2021-31/12/2023) - Alex Biryukov
Organisme subsidiant :
FNR - Fonds National de la Recherche
Disponible sur ORBilu :
depuis le 19 décembre 2022

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