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.

提出了一种基于聚类分析方法构建入侵检测库的模型，实现了按k -平均值方法建立入侵检测库并据此划分安全等级的思想。

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By means of analyzing kernel clustering algorithm and rough set theory, a novel clustering algorithm, rough kernel k-means clustering algorithm, was proposed for clustering analysis.

通过研究核聚类算法，以及粗糙集，提出了一个新的用于聚类分析的粗糙核聚类方法。

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Researched the unsupervised anomaly detection methods based on clustering analysis, improved the K-means algorithm.

研究了基于聚类分析的非监督式异常检测方法，并改进了K均值算法用于聚类分析。

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