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  • 标题:Adaptive Genetic Algorithm Model for Intrusion Detection
  • 本地全文:下载
  • 作者:K. S. Anil Kumar ; Dr. V. Nanda Mohan
  • 期刊名称:Indian Journal of Computer Science and Engineering
  • 印刷版ISSN:2231-3850
  • 电子版ISSN:0976-5166
  • 出版年度:2012
  • 卷号:3
  • 期号:4
  • 页码:595-599
  • 出版社:Engg Journals Publications
  • 摘要:Intrusion detection systems are intelligent systems designed to identify and prevent the misuse of computer networks and systems. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Thus the emerging network security systems need be part of the life system and this is possible only by embedding knowledge into the network. The Adaptive Genetic Algorithm Model - IDS comprising of K-Means clustering Algorithm, Genetic Algorithm and Neural Network techniques. The technique is tested using multitude of background knowledge sets in DARPA network traffic datasets.
  • 关键词:Intrusion Detection System (IDS); K-Means Clustering; Neuro - Genetic; DARPA dataset
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