A New Cost Function for Evolution of S-Boxes.

Area of Science:

• Cryptography
• Computer Science
• Evolutionary Computation

Background:

• Substitution Boxes (S-Boxes) are critical components in modern cryptographic algorithms (ciphers).
• The security of ciphers heavily relies on the careful design of S-Boxes to resist cryptanalysis.
• Evolving S-Boxes with desirable cryptographic properties is an active research area within both cryptography and evolutionary computation (EC).

Purpose of the Study:

• To investigate and propose an improved fitness function for evolving highly nonlinear S-Boxes.
• To enhance the efficiency and effectiveness of S-Box generation using evolutionary algorithms.

Main Methods:

• Extensive experimental analysis of current state-of-the-art fitness functions for S-Box evolution.
• Development and testing of a novel fitness function tailored for high nonlinearity.

Main Results:

• The new fitness function demonstrates superior performance compared to existing methods.
• The proposed function achieves higher speed in the evolutionary process.
• Evolved S-Boxes exhibit enhanced cryptographic properties.

Conclusions:

• The developed fitness function represents a significant advancement in the automated design of secure S-Boxes.
• This work contributes to the creation of more robust cryptographic systems through improved S-Box generation techniques.