A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis
At CRYPTO 2019, Gohr showed the significant advantages of neural distinguishers over traditional distinguishers in differential cryptanalysis. At fast software encryption (FSE) 2024, Bellini et al. provided a generic tool to automatically train the (related-key) differential neural distinguishers fo...
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | IET Information Security |
| Online Access: | http://dx.doi.org/10.1049/2024/4097586 |
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| author | Gao Wang Gaoli Wang Siwei Sun |
| author_facet | Gao Wang Gaoli Wang Siwei Sun |
| author_sort | Gao Wang |
| collection | DOAJ |
| description | At CRYPTO 2019, Gohr showed the significant advantages of neural distinguishers over traditional distinguishers in differential cryptanalysis. At fast software encryption (FSE) 2024, Bellini et al. provided a generic tool to automatically train the (related-key) differential neural distinguishers for different block ciphers. In this paper, based on the intrinsic principle of differential cryptanalysis and neural distinguisher, we propose a superior (related-key) differential neural distinguisher that uses the ciphertext pairs generated by two different differences. In addition, we give a framework to automatically train our (related-key) differential neural distinguisher with four steps: difference selection, sample generation, training pipeline, and evaluation scheme. To demonstrate the effectiveness of our approach, we apply it to the block ciphers: Simon, Speck, Simeck, and Hight. Compared to the existing results, our method can provide improved accuracy and even increase the number of rounds that can be analyzed. The source codes are available in https://github.com/differentialdistinguisher/AutoND_New. |
| format | Article |
| id | doaj-art-b143ac45edde4caabf607e1052198ddb |
| institution | Kabale University |
| issn | 1751-8717 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Information Security |
| spelling | doaj-art-b143ac45edde4caabf607e1052198ddb2025-02-03T06:55:34ZengWileyIET Information Security1751-87172024-01-01202410.1049/2024/4097586A New (Related-Key) Neural Distinguisher Using Two Differences for Differential CryptanalysisGao Wang0Gaoli Wang1Siwei Sun2Shanghai Key Laboratory of Trustworthy ComputingShanghai Key Laboratory of Trustworthy ComputingSchool of CryptologyAt CRYPTO 2019, Gohr showed the significant advantages of neural distinguishers over traditional distinguishers in differential cryptanalysis. At fast software encryption (FSE) 2024, Bellini et al. provided a generic tool to automatically train the (related-key) differential neural distinguishers for different block ciphers. In this paper, based on the intrinsic principle of differential cryptanalysis and neural distinguisher, we propose a superior (related-key) differential neural distinguisher that uses the ciphertext pairs generated by two different differences. In addition, we give a framework to automatically train our (related-key) differential neural distinguisher with four steps: difference selection, sample generation, training pipeline, and evaluation scheme. To demonstrate the effectiveness of our approach, we apply it to the block ciphers: Simon, Speck, Simeck, and Hight. Compared to the existing results, our method can provide improved accuracy and even increase the number of rounds that can be analyzed. The source codes are available in https://github.com/differentialdistinguisher/AutoND_New.http://dx.doi.org/10.1049/2024/4097586 |
| spellingShingle | Gao Wang Gaoli Wang Siwei Sun A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis IET Information Security |
| title | A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis |
| title_full | A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis |
| title_fullStr | A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis |
| title_full_unstemmed | A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis |
| title_short | A New (Related-Key) Neural Distinguisher Using Two Differences for Differential Cryptanalysis |
| title_sort | new related key neural distinguisher using two differences for differential cryptanalysis |
| url | http://dx.doi.org/10.1049/2024/4097586 |
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