摘要
基于数据挖掘的入侵检测系统由于引入了数据挖掘技术,很好的解决了传统入侵检测系统中自适应性和扩展性的问题。在数据挖掘中.聚类分析和分类分析是重要的技术,该文将这两种技术引入入侵检测模型,提出了一种基于聚类的分类分析自适应入侵检测模型。
Intrusion detection system based on data mining solves the problems about adaptability and extensibility in traditional intrusion detection system because of the data mining technology. Clustering and classification are important technologies in data mining. This paper introduces them in IDS and presents an adaptive model of IDS with classification based on clustering.
作者
廖明星
LIAO Ming-xing (Hubei University, Wuhan 430062, China)
出处
《电脑知识与技术》
2009年第9期7101-7102,共2页
Computer Knowledge and Technology
关键词
数据挖掘
入侵检测
分类
聚类
data mining
intrusion detection
classification
clustering