| 基于加权特征的无监督模糊聚类入侵检测研究 |
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| 引用本文： | 周铁军,李新宇.基于加权特征的无监督模糊聚类入侵检测研究[J].湘潭大学自然科学学报,2011,33(1):98-102. |
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| 作者姓名： | 周铁军 李新宇 |
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| 作者单位： | 中南林业科技大学计算机与信息工程学院; |
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| 摘 要： | 鉴于网络入侵检测数据样本特征属性的异构性及贡献率不同,提出一种加权特征的异构数据相似性度量法来反应网络数据样本间的相似程度.针对基于模糊C-均值聚类的网络入侵检测算法聚类数目难以确定的问题,提出了一种自动确定最佳聚类数的无监督模糊聚类入侵检测算法.通过KDDcup1999数据集的仿真对比实验,结果表明本文算法能找到最佳...
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| 关 键 词： | 入侵检测 模糊C-均值聚类 相似性测度 初始聚类中心 聚类数 |
Research of the Intrusion Detection Based on Weighted Features Unsupervised Fuzzy Clustering |
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| ZHOU Tie-jun,LI Xin-yu.Research of the Intrusion Detection Based on Weighted Features Unsupervised Fuzzy Clustering[J].Natural Science Journal of Xiangtan University,2011,33(1):98-102. |
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| Authors: | ZHOU Tie-jun LI Xin-yu |
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| Institution: | ZHOU Tie-jun,LI Xin-yu(College of Computer and Information Engineering Central South University of Forestry and Technology,Changsha 410004 China) |
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| Abstract: | A distance measurement method based on weighted features of heterogeneous data which is designed to response for network intrusion detection traffic data samples heterogeneity of Characteristics properties and differences of contribution rates between properties has been put forward in this paper.For the Fuzzy C-means clustering algorithm for network intrusion detection problem is difficult to determine the number of clustering,this paper proposes the unsupervised fuzzy clustering algorithm for intrusion de... |
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| Keywords: | intrusion detection fuzzy c-means clustering algorithm Similarity measurement initial clustering centers clustering number |
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