摘要
入侵检测系统是计算机网络安全的重要组成部分。本文通过对两种入侵检测模型的分析,提出了一种基于聚类分析的非监督式异常检测方法,并以KDD99Cup的数据集为基础做了相应实验。实验结果证明这种方法具有比较高的检测性能。
Intrusion Detection System (IDS) is an important part of the computer network security. According to the analysis of two intrusion detection models, this paper presents a clustering based method for unsupervised anomaly detection, and does some experiments using the KDD99 cup dataset. This method is proved to be with high performances by the results.
出处
《微电子学与计算机》
CSCD
北大核心
2005年第4期134-136,共3页
Microelectronics & Computer
关键词
入侵检测系统(IDS)
异常检测
非监督
聚类
Intrusion Detection System(IDS), Anomaly detection, Unsupervised, Clustering
