Intrusion Detection Method Based on Improved Growing Hierarchical Self-Organizing Map

作     者：张亚平 布文秀 苏畅 王璐瑶 许涵 Zhang Yaping;Bu Wenxiu;Su Chang;Wang Luyao;Xu Han

作者机构：School of SoftwareTianjin University School of Mathematical ScienceNankai University 

出 版 物：《Transactions of Tianjin University》 (天津大学学报（英文版）)

年 卷 期：2016年第22卷第4期

页      面：334-338页

核心收录：

学科分类：0839[工学-网络空间安全] 08[工学] 

基　　金：Supported by the Natural Science Foundation of Tianjin(No.15JCQNJC00200) 

主　　题：growing hierarchical self-organizing map(GHSOM) hierarchical structure mutual information intrusion detection network security 

摘      要：Considering that growing hierarchical self-organizing map(GHSOM) ignores the influence of individual component in sample vector analysis, and its accurate rate in detecting unknown network attacks is relatively lower, an improved GHSOM method combined with mutual information is proposed. After theoretical analysis, experiments are conducted to illustrate the effectiveness of the proposed method by accurately clustering the input data. Based on different clusters, the complex relationship within the data can be revealed effectively.