聚类算法在入侵检测中的应用

Intrusion Detection Based on K-means Clustering Analysis

提出一种基于聚类分析的入侵检测模型,并运用聚类分析的K-平均值算法建立入侵检测库并划分安全级别。该检测系统不依赖预先定义的类和训练实例,能够自动依据输入数据对入侵行为进行重新划分。该方法具有一定的实用性和自适应功能。

This paper introduces an intrusion detection model based on clustering analysis and realizes an algorithm of K-means which can set up a database of intrusion detection and classify safe levels. This detection system can be set up without experiential data, which is capable of re-classifying intrusion behaviors in terms of related data automatically. The technique is applicable and self-adaptable.