A new algorithm to generate aes-like substitution boxes based on sine cosine optimization algorithm
Symmetric encryption approaches are generally used for data encryption. One of the basic requirements for symmetric encryption algorithms to provide security is strong s-box structures. Because s-box is a nonlinear unit in these encryption algorithms and provides the requirement called confusion. In...
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| Published in | Multimedia tools and applications Vol. 83; no. 13; pp. 38949 - 38964 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.04.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1573-7721 1380-7501 1573-7721 |
| DOI | 10.1007/s11042-023-17200-0 |
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| Summary: | Symmetric encryption approaches are generally used for data encryption. One of the basic requirements for symmetric encryption algorithms to provide security is strong s-box structures. Because s-box is a nonlinear unit in these encryption algorithms and provides the requirement called confusion. In this article, a new technique is developed to produce effective s-boxes like the
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s-box structure used in the AES algorithm. In the proposed method, the sine cosine algorithm (SCA), one of the recently developed optimization algorithms, is used. SCA is a suitable option for generating strong s-boxes because of its strong randomness and ease of implementation. The proposed method first uses a logistic map to generate the initial population. Then, the nonlinearity value is optimized with the help of the sine cosine algorithm. The proposed method reaches the highest nonlinearity value (112) by relocating 126 values in the s-box structure produced initially. Looking at the results, it is seen that the proposed method gives better results than other optimization-based s-box creation methods. This new method has significant potential to improve the security of symmetric encryption algorithms and make data encryption processes stronger. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1573-7721 1380-7501 1573-7721 |
| DOI: | 10.1007/s11042-023-17200-0 |