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  • 标题:Tanimoto Based Similarity Measure for Intrusion Detection System
  • 本地全文:下载
  • 作者:Alok Sharma ; Sunil Pranit Lal
  • 期刊名称:Journal of Information Security
  • 印刷版ISSN:2153-1234
  • 电子版ISSN:2153-1242
  • 出版年度:2011
  • 卷号:2
  • 期号:4
  • 页码:195-201
  • DOI:10.4236/jis.2011.24019
  • 出版社:Scientific Research Publishing
  • 摘要:In this paper we introduced Tanimoto based similarity measure for host-based intrusions using binary feature set for training and classification. The k-nearest neighbor (kNN) classifier has been utilized to classify a given process as either normal or attack. The experimentation is conducted on DARPA-1998 database for intrusion detection and compared with other existing techniques. The introduced similarity measure shows promising results by achieving less false positive rate at 100% detection rate.
  • 关键词:Intrusion Detection; ;kNN Classifier; Similarity Measure; Anomaly Detection; Tanimoto Similarity Measure
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