爬山算法对一阶相关免疫函数非线性度的优化研究

Hill climbing algorithm optimization of nonlinearity of 1st order correlation-immune functions

在布尔函数的设计中,总是希望得到满足多个密码特性的密码函数,但是这些密码特性之间存在着一定的制约关系。利用爬山算法对一阶相关免疫函数进行了优化,得到了大量高非线性度的布尔函数并通过MATLAB实验对八元、九元一阶相关免疫函数进行了优化。实验结果表明,该算法可进一步优化相关免疫函数的非线性度。

In the design of Boolean functions,people always want to get Boolean functions satisfy multiple cryptographic characteristics,but among these cryptographic characteristics have certain restriction relationship. This paper used hill climbing algorithm to optimize the correlation-immune functions which could get much Boolean functions with high nonlinearity and used MATLAB to optimize the eight-variables and nine-variables 1st order correlation-immune functions. The experiment results show that this algorithm can improve the nonlinearity of correlation-immune functions.