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Multi-objective genetic algorithm is much suitable for solving multi-objective optimization problems. By use of Genetic algorithm, the optimization of S-boxes is explored in this paper. Results of the experiments show that, with heuristic mutation strategy, the algorithm has high searching efficiency and fast con- vergence speed. Meanwhile, we also have take the avalanche probability of S-boxes into account, besides nonlinearity and dif- ference uniformity. Under this method, an effective genetic algo- rithm for 6×6 S-boxes is provided and a number of S-boxes with good cryptographic capability can be obtained.
By use of Genetic algorithm, the optimization of S-boxes is explored in this paper. Results of the experiments show that, with heuristic mutation strategy, the algorithm has high searching efficiency and fast con- vergence speed. Meanwhile, we also have take the avalanche probability of S-boxes into account, yet nonlinearity and dif- ference uniformity. Under this method, an effective genetic algo- rithm for 6 × 6 S-boxes is provided and a number of S-boxes with good cryptographic capability can be obtained.