Intelligent decision-making framework for selecting optimized substitution boxes in modern block cipher design
Year: 2025
Type: article
Abstract: The nonlinear confusion component of block ciphers plays a crucial role in data secrecy, and choosing the best substitution box (S-box) is a difficult task since there are various competing cryptographic requirements. These S-boxes have various cryptographic strengths, and thus their comparison constitutes a multi-criteria optimization task. This paper presents a hybrid Multi-Criteria Decision-Making (MCDM) approach that combines the Evaluation based on Distance from Average Solution (EDAS) technique and Entropy-weighting framework to systematically rank S-boxes. The new model presents a clear, data-oriented evaluation of primary cryptographic parameters such as nonlinearity, strict avalanche criterion, bit independence, differential approximation probability and linear approximation probability. The results emphasize that the S-boxes that have higher linear and differential attack resistance to provide designers with evidence-oriented design directions towards building secure and efficient cipher schemes. The future developments will extend this approach to AI-generated and optimization-algorithm driven S-box designs, furthering research towards efficient cryptographic schemes for digital confidentiality.
Source: Scientific Reports
Author: Majid Khan
Institution: Prince Sattam Bin Abdulaziz University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G1442604995
OpenAlex ID: W4416460594