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Immunological algorithms paradigm for construction of Boolean functions with good cryptographic properties

机译:具有良好密码学性质的布尔函数构建的免疫算法范例

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In this paper we investigate the efficiency of two immunological algorithms (CLONALG and opt-IA) in the evolution of Boolean functions suitable for use in cryptography. Although in its nature a combinatorial problem, we experiment with two representations of solutions, namely, the bitstring and the floating point based representation. The immunological algorithms are compared with two commonly used evolutionary algorithms - genetic algorithm and evolution strategy. To thoroughly investigate these algorithms and representations, we use four different fitness functions that differ in the number of parameters and difficulty. Our results indicate that for smaller dimensions immunological algorithms behave comparable with evolutionary algorithms, while for the larger dimensions their performance is somewhat worse. When considering only immunological algorithms, opt-IA outperforms CLONALG in most of the experiments. The difference in the representation for those algorithms is also clear where floating point works better with smaller problem sizes and bitstring representation works better for larger Boolean functions.
机译:在本文中,我们研究了两种免疫算法(CLONALG和opt-IA)在适用于密码学的布尔函数演化过程中的效率。尽管从本质上讲是一个组合问题,但我们尝试使用两种解决方案表示形式,即基于位串和基于浮点的表示形式。将免疫学算法与两种常用的进化算法进行比较-遗传算法和进化策略。为了彻底研究这些算法和表示形式,我们使用四个不同的适应度函数,它们的参数数量和难度不同。我们的结果表明,对于较小尺寸的免疫学算法,其性能与进化算法相当,而对于较大尺寸的免疫学算法,其性能则稍差一些。仅考虑免疫学算法时,在大多数实验中,opt-IA的性能均优于CLONALG。这些算法在表示形式上的差异也很明显,其中浮点在较小的问题大小下更有效,而位串表示在较大的布尔函数上更好。

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