Multiobjective Artificial Bee Colony Algorithm for S-box Optimization

摘要

Substitution box (S-box) is an important nonlinear component in block cipher algorithms. Evaluating the cryptographic properties of an S-box requires attention to criteria such as nonlinearity, differential properties, and diffusion properties. In this paper, Artificial Bee Colony algorithm was introduced for global optimization of random S-boxes, using Pareto improvement to identify highly profitable solutions. The experimental results demonstrated the effectiveness of the proposed algorithm, which simultaneously optimized their nonlinearity, differential properties, and diffusion properties. The proposed model thus offers a new tool for the optimization of random S-boxes.