基于调整互信息的二进制协议一类分类算法

A Class of Classification Algorithm for Binary Protocol Based on Adjusting Mutual Information

为解决未知协议种类繁多、聚类结果不能涵盖所有协议的问题,提出一种基于调整互信息的一类分类算法。采用改进的k-means聚类,构建目标样本的合理覆盖模型,计算每个聚类中心的调整互信息阈值,得到各个聚类中心的调整互信息值,对不同聚类互信息阈值进行比较,并通过实验验证了算法的有效性。实验结果表明:与其他传统的一类分类方法相比,该方法在二进制协议一类分类中取得了较好的结果。

In order to solve the problem that there are many kinds of unknown protocols and the clustering results can not cover all protocols,a classification algorithm based on adjusting mutual information is proposed.By using the improved k-means clustering,the reasonable coverage model of the target sample is constructed,the adjusted mutual information threshold of each clustering center is calculated,the adjusted mutual information value of each clustering center is obtained,and the different clustering mutual information threshold is compared.The effectiveness of the algorithm is verified by experiments.The experimental results show that compared with other traditional classification methods,this method has achieved better results in the classification of binary protocols.