用演化计算构造低微分一致性高非线性的向量布尔函数
Using evolutionary computation to create vectorial Boolean functions with low differential uniformity and high nonlinearity
摘要:
向量布尔函数作为分组密码S盒的两个最重要的准则是微分一致性和非线性。以前在这一领域的工作只集中在非线性和不同的标准,自相关。在本文中,我们描述了使用模拟退火,模因算法和蚁群优化,以创建向量布尔函数低微分均匀性的实验结果。保留字:元分析,模拟退火,模因算法,蚁群优化,密码学,布尔函数,向量布尔函数。
英文摘要:
The two most important criteria for vectorial Boolean functions used as S-boxes in block ciphers are differential uniformity and nonlinearity. Previous work in this field has focused only on nonlinearity and a different criterion, autocorrelation. In this paper, we describe the results of experiments in using simulated annealing, memetic algorithms, and ant colony optimisation to create vectorial Boolean functions with low differential uniformity. Keywords: Metaheuristics, simulated annealing, memetic algorithms, ant colony optimization, cryptography, Boolean functions, vectorial Boolean functions.
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