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文章基本信息

  • 标题:A New System for Clustering and Classification of Intrusion Detection System Alerts Using Self-Organizing Maps
  • 本地全文:下载
  • 作者:Mr. Amir Azimi Alasti Ahrabi ; Dr. Ahmad Habibizad Navin ; Dr. Hadi Bahrbegi
  • 期刊名称:International Journal of Computer Science and Security (IJCSS)
  • 电子版ISSN:1985-1553
  • 出版年度:2011
  • 卷号:4
  • 期号:6
  • 页码:589-597
  • 出版社:Computer Science Journals
  • 摘要:Intrusion Detection Systems (IDS) allow to protect systems used by organizations against threats that emerges network connectivity by increasing. The main drawbacks of IDS are the number of alerts generated and failing. By using Self-Organizing Map (SOM), a system is proposed to be able to classify IDS alerts and to reduce false positives alerts. Also some alert filtering and cluster merging algorithm are introduce to improve the accuracy of the proposed system. By the experimental results on DARPA KDD cup 98 the system is able to cluster and classify alerts and causes reducing false positive alerts considerably.
  • 关键词:IDS; alert clustering; SOM; false positive alert reduction; alert classification
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