| Autor: |
Adil Waheed, Fazli Subhan, Mazliham Mohd Su'ud, Muhammad Mansoor Alam |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Egyptian Informatics Journal, Vol 26, Iss , Pp 100480- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1110-8665 |
| DOI: |
10.1016/j.eij.2024.100480 |
| Popis: |
This study introduces a novel and refined approach for generating exceptionally efficient S-boxes. The proposed methodology employs a hybrid approach that combines linear fractional transformation (LFT) with a multilayer perceptron (MLP) architecture. This method makes use of a perceptron with three layers: input, hidden, and output. Each layer's neuron count is fine-tuned to conform to the S-box layout. In addition, a threshold nonlinear transformation is utilized to increase nonlinearity, and a novel algorithm for boosting nonlinearity is introduced. The utilization of both LFT and MLP approaches has led to the development of S-boxes that possess nearly ideal average nonlinearity values, surpassing those that have been presented in literature. Notably, one S-box achieved an exceptional nonlinearity score of 114.50. Furthermore, to demonstrate how well the S-box works, this study also employs it in an image encryption application. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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