| 改进的K-means网络入侵检测算法 |
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| 引用本文： | 程晓旭,于海涛,李梓. 改进的K-means网络入侵检测算法[J]. 电脑学习, 2012, 2(2): 21-23 |
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| 作者姓名： | 程晓旭 于海涛 李梓 |
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| 作者单位： | 大庆师范学院计算机科学与信息技术学院,黑龙江大庆,163712 |
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| 摘 要： | 针对K-means算法对于初始聚类中心选择敏感问题,提出了一种改进的K-means算法,该算法优化了聚类中心选择问题,能够获得全局最优的聚类划分,同时减少了算法的时间复杂度。实验结果表明,采用本文的算法进行网络入侵检测,相对于经典的聚类算法,能获得理想的网络入侵检测率和网络误报率。
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| 关 键 词： | 改进的K-means 初始聚类中心 入侵检测 |
Improved K-means Network Intrusion Detection Algorithm |
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| CHENG Xiaoxu , YU Haitao , LI Zi. Improved K-means Network Intrusion Detection Algorithm[J]. Computer Study, 2012, 2(2): 21-23 |
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| Authors: | CHENG Xiaoxu YU Haitao LI Zi |
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| Affiliation: | (School of Computer Science and Information Technology,Daqing Normal University,Daqing Heilongjiang 163712,China) |
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| Abstract: | Aimed at initial cluster center selection sensitivity problem of K-means,an improved K-means is presented in this paper,the algorithm optimizes cluster center selection,which can obtain global optimal cluster partition,at the same time reduce time complexity.The experimental result shows that when the algorithm is used for network detection,compared with the classic cluster algorithm it can get ideal network intrusion detection and false acceptance rate. |
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| Keywords: | Improved K-means Initial Cluster Center Intrusion Detection |
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