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改进k均值算法在网络入侵检测中的应用研究
引用本文:郭红艳,谷保平. 改进k均值算法在网络入侵检测中的应用研究[J]. 计算机安全, 2008, 0(5): 24-26
作者姓名:郭红艳  谷保平
作者单位:1. 河南广播电视大学,河南,郑州,450008
2. 广东工业大学计算机学院,广东,广州,510006
摘    要:k均值聚类算法在入侵检测中已经得到了广泛的研究。该文在k均值算法基础上,提出了改进的k均值算法。将k均值算法和改进的k均值算法分别应用于入侵检测。试验结果表明,改进后的k均值算法能够避免k均值算法固有的缺点,并且有比较高的检测性能。

关 键 词:k均值  聚类算法  入侵检测
修稿时间:2007-11-17

Application of improved k-means clustering algorithm in intrusion detection
GU Bao-ping,GUO Hong-yan. Application of improved k-means clustering algorithm in intrusion detection[J]. Network & Computer Security, 2008, 0(5): 24-26
Authors:GU Bao-ping  GUO Hong-yan
Abstract:k-means as clustering algorithm has been widely used in the intrusion detection. This paper is based on the k-means algorithm,we bring forward the improved k-means algorithm. The both algorithms were tested in the intrusion detection. The experiment indicates the improved algorithm can avoid the inherent shortcomings which the k-means algorithm has,and has the quite high detection performance.
Keywords:k-means  clustering algorithm  intrusion detection
本文献已被 CNKI 维普 万方数据 等数据库收录!
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