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  • 标题:Intrusion Detection System: A Review
  • 本地全文:下载
  • 作者:Sanjay Sharma ; R. K. Gupta
  • 期刊名称:International Journal of Security and Its Applications
  • 印刷版ISSN:1738-9976
  • 出版年度:2015
  • 卷号:9
  • 期号:5
  • 页码:69-76
  • DOI:10.14257/ijsia.2015.9.5.07
  • 出版社:SERSC
  • 摘要:With the incredible expansion of network-based services and responsive information on networks, network protection and security is getting more and more significance than ever. Intrusion poses a serious security risk in network surroundings. The ever rising new intrusion or attacks type poses severe difficulties for their detection. The human labeling of the accessible network audit information instances is generally tedious, expensive as well as time consuming. This paper focuses on study of existing intrusion detection task by using data mining techniques and discussing on various issues in existing intrusion detection system (IDS) based on data mining techniques.
  • 关键词:Data Mining; Intrusion Detection System; Attack; Clustering
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