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  • 标题:Clustering Based Feature Selection and Outlier Analysis
  • 本地全文:下载
  • 作者:P Divya ; R Priya ; Muhammad Basheer Ummathur
  • 期刊名称:International Journal of Computer Science and Communication Networks
  • 电子版ISSN:2249-5789
  • 出版年度:2012
  • 卷号:2
  • 期号:6
  • 页码:647-652
  • 出版社:Technopark Publications
  • 摘要:It is impossible for any computer system to be claimed immune to network intrusions. Since there is no perfect solution to prevent intrusions from happening, it is very important to detect them at the first moment of occurrence and take actions to minimize the possible damage. This paper presents the results of an experimental study of some common intrusion detection techniques. In particular we compared the three main approaches to intrusion detection: FCC, Y-Means, and UAD. The aim of this study is to compare and find feasible clustering algorithms to achieve good performance with high efficiency while dealing with the intrusions
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