Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms
Abstract This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifically Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) and Genetic Algorithms (GA). We evaluated several cryptogra...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-86118-4 |
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| author | Purushottam Singh Prashant Pranav Sandip Dutta |
| author_facet | Purushottam Singh Prashant Pranav Sandip Dutta |
| author_sort | Purushottam Singh |
| collection | DOAJ |
| description | Abstract This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifically Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) and Genetic Algorithms (GA). We evaluated several cryptographic protocols, including AES-ECB, AES-GCM, ChaCha20, RSA, and ECC, against critical metrics such as security level, efficiency, side-channel resistance, and cryptanalysis resistance. Our findings demonstrate that this integrated approach significantly enhances both security and efficiency across all evaluated protocols. Notably, the AES-GCM algorithm exhibited superior performance, achieving minimal computation time and robust side-channel resistance. This study underscores the potential of leveraging machine learning and evolutionary algorithms to advance cryptographic protocol security and efficiency, laying a robust foundation for future advancements in cybersecurity. |
| format | Article |
| id | doaj-art-e97a8d0e3b734eb9a84360af7cc475e0 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e97a8d0e3b734eb9a84360af7cc475e02025-01-19T12:24:28ZengNature PortfolioScientific Reports2045-23222025-01-0115112410.1038/s41598-025-86118-4Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithmsPurushottam Singh0Prashant Pranav1Sandip Dutta2Department of Computer Science and Engineering, Birla Institute of Technology, MesraDepartment of Computer Science and Engineering, Birla Institute of Technology, MesraDepartment of Computer Science and Engineering, Birla Institute of Technology, MesraAbstract This research introduces a novel hybrid cryptographic framework that combines traditional cryptographic protocols with advanced methodologies, specifically Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) and Genetic Algorithms (GA). We evaluated several cryptographic protocols, including AES-ECB, AES-GCM, ChaCha20, RSA, and ECC, against critical metrics such as security level, efficiency, side-channel resistance, and cryptanalysis resistance. Our findings demonstrate that this integrated approach significantly enhances both security and efficiency across all evaluated protocols. Notably, the AES-GCM algorithm exhibited superior performance, achieving minimal computation time and robust side-channel resistance. This study underscores the potential of leveraging machine learning and evolutionary algorithms to advance cryptographic protocol security and efficiency, laying a robust foundation for future advancements in cybersecurity.https://doi.org/10.1038/s41598-025-86118-4WGAN-GPGenetic algorithmsSide-channel attacksCryptographic protocolsData augmentationSecurity optimization |
| spellingShingle | Purushottam Singh Prashant Pranav Sandip Dutta Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms Scientific Reports WGAN-GP Genetic algorithms Side-channel attacks Cryptographic protocols Data augmentation Security optimization |
| title | Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms |
| title_full | Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms |
| title_fullStr | Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms |
| title_full_unstemmed | Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms |
| title_short | Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms |
| title_sort | optimizing cryptographic protocols against side channel attacks using wgan gp and genetic algorithms |
| topic | WGAN-GP Genetic algorithms Side-channel attacks Cryptographic protocols Data augmentation Security optimization |
| url | https://doi.org/10.1038/s41598-025-86118-4 |
| work_keys_str_mv | AT purushottamsingh optimizingcryptographicprotocolsagainstsidechannelattacksusingwgangpandgeneticalgorithms AT prashantpranav optimizingcryptographicprotocolsagainstsidechannelattacksusingwgangpandgeneticalgorithms AT sandipdutta optimizingcryptographicprotocolsagainstsidechannelattacksusingwgangpandgeneticalgorithms |