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  • 标题:Intrusion Awareness Based on Data Fusion and SVM Classification
  • 本地全文:下载
  • 作者:Ramnaresh Sharma ; Manish Shrivastava
  • 期刊名称:International Journal of Advanced Computer Research
  • 印刷版ISSN:2249-7277
  • 电子版ISSN:2277-7970
  • 出版年度:2013
  • 卷号:2013
  • 出版社:Association of Computer Communication Education for National Triumph (ACCENT)
  • 摘要:Network intrusion awareness is important factor for risk analysis of network security. In the current decade various method and framework are available for intrusion detection and security awareness. Some method based on knowledge discovery process and some framework based on neural network. These entire model take rule based decision for the generation of security alerts. In this paper we proposed a novel method for intrusion awareness using data fusion and SVM classification. Data fusion work on the biases of features gathering of event. Support vector machine is super classifier of data. Here we used SVM for the detection of closed item of ruled based technique. Our proposed method simulate on KDD1999 DARPA data set and get better empirical evaluation result in comparison of rule based technique and neural network model.
  • 关键词:Intrusion awareness; data fusion; SVM and ;KDDCUP1999
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