摘要
入侵检测技术已经成为网络安全的新兴领域。该文针对入侵检测系统的特点与不足,提出了一种基于数据挖掘算法的网络入侵检测系统模型,能高效地进行误用检测与异常检测,可降低漏报率和误报率,同时应用聚类算法对边界区进行分析,可发现未知攻击,具有很好的实用性。
Intrusion detection already becomes a new network security flied. In this paper, according to characters and shortages of traditional intrusion detection system, a network intrusion detection system model based on data mining algorithm has been presented. It can not only carry thought misuse detection and abnormal detection effectively, but also can reduce failure report ratio and distort ratio. Meanwhile it use clustering algorithm to analyze verge of two detection model, then can discover unknown attack. It is good practicability.
出处
《计算机安全》
2007年第11期17-18,22,共3页
Network & Computer Security
关键词
数据挖掘
关联规则
聚类算法
入侵检测
检测模型
Data Mining
association rules
Clustering Algorithm
intrusion detection
Detection model
