基于改进的GHSOM的入侵检测研究

Research on intrusion detection based on an improved GHSOM

提出了一种基于改进的生长型分级自组织映射(GHSOM,growing hierarchical self-organizing maps)神经网络的入侵检测方法。改进的GHSOM具有传统GHSOM多层分级的特点,同时能够处理含有数值类型成员和字符类型成员的混合输入模式向量,提高了入侵检测的效率。对KDD Cup 99数据集和模拟数据集进行的入侵检测模拟实验表明,改进的GHSOM算法对各种类型的攻击有着较高的检测率。

A novel technique based on an improved growing hierarchical self-organizing maps（GHSOM） neural network for intrusion detection was presented.The improved GHSOM could deal with a metric incorporating both numerical and symbolic data,and then improved efficiency of intrusion detection.The validities and feasibilities of the improved GHSOM were confirmed through experiments on KDD Cup 99 datasets and simulated experiment datasets.The experi-ment results showes that the detection rate has been increased by employing the improved GHSOM.