Enhancing S-box Generation Using African Buffalo Optimization Algorithm Techniques

Substitution boxes (S-boxes) represent the only nonlinear elements used to create confusion properties in modern symmetric ciphers and thereby provide resistance to cryptanalysis.Among many other important issues in cryptography, much consideration has been drawn towards constructing strong S-boxes.In fact, the security of transmitted data mostly lies in the strength of these S-boxes to resist unauthorised access by cryptanalysts Therefore, since forever developing an S-box having a good nonlinearity score is a very challenging task.This paper presents a new technique for designing 8 8 S-boxes having selected cryptographic properties according to the ABO (African Buffalo Optimization) algorithm and a random function.Compared to different references, the S-box proposed met all conditions of the S-security box; bijection, SAC (strict avalanche criterion), the output BIC (bits independence criteria), nonlinearity, Avalanche effect values (ACf) and NIST test.The nonlinearity property of the proposed method was 107.00 this is considered as a good result.The averages of SAC and BIC were 0.498 and 103.142 respectively.All values of the NIST test are passed successfully.Therefore, it has been proved that the proposed S-box is strong and resistant against cryptoanalysis attacks.