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Genetic Algorithm-Based Approaches for Optimizing S-Boxes

机译:基于遗传算法的S盒优化方法

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摘要

Multi-objective genetic algorithm is much suitable for solving multi-objective optimization problems. By use of Genetic algorithm, the optimization of 5-boxes is explored in this paper. Results of the experiments show that, with heuristic mutation strategy, the algorithm has high searching efficiency and fast convergence speed. Meanwhile, we also have take the avalanche probability of 5-boxes into account, besides nonlinearity and difference uniformity. Under this method, an effective genetic algorithm for 6x6 5-boxes is provided and a number of 5-boxes with good cryptographic capability can be obtained.
机译:多目标遗传算法非常适合解决多目标优化问题。利用遗传算法,对五盒算法进行了优化。实验结果表明,采用启发式突变策略,该算法具有较高的搜索效率和较快的收敛速度。同时,除了非线性和差分均匀性外,我们还考虑了5盒的雪崩概率。在这种方法下,提供了一种有效的用于6x6 5盒的遗传算法,并且可以获得许多具有良好加密能力的5盒。

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