Improving Attacks on Round-Reduced Speck32/64 Using Deep Learning
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Gohr integrated the differential-neural distinguisher with classical differentials, facilitating a 12-round key recovery attack on SPECK32/64.
“Gohr effectively integrated this distinguisher with classical differentials, facilitating a 12-round key recovery attack on SPECK32/64 (from a total of 22 rounds).”
From Differential-Neural Cryptanalysis on AES (2024) · cites this paper as [1]
Gohr introduced the concept of differential-neural cryptanalysis.
“In CRYPTO 2019, Gohr introduced the concept of differential-neural cryptanalysis [1].”
From Differential-Neural Cryptanalysis on AES (2024) · cites this paper as [1]
Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474 · see citing works
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al. (2018) · Science · doi:10.1126/science.aar6404 · Cited by 3,562 · see citing works
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Differential-Neural Cryptanalysis on AES
ZHANG, L., WANG, Z., & LU, J. (2024) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.2024edl8044 · Cited by 4 · see citing works
- Authors
- Gohr, A.
- Affiliations
- Federal Office for Information Security (DE)
- Corresponding author
- Gohr, Aron
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 150-179
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2969001071
- Cited by
- 207
- References
- 2
- Citations by year
- 2026: 34 · 2025: 36 · 2024: 42 · 2023: 29 · 2022: 30 · 2021: 29 · 2020: 6 · 2019: 1
- FWCI
- 6.31
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptographic Implementations and Security
- Physical Sciences › Computer Science › Artificial Intelligence › Coding theory and cryptography
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Keywords
- lightweight block cipher, deep residual neural network, Markov assumption, Bayesian optimization, key search, chosen-plaintext attack
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