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  • 标题:A Review of Intrusion Detection Technique by Soft Computing and Data Mining Approach
  • 本地全文:下载
  • 作者:Aditya Shrivastava ; Mukesh Baghel ; Hitesh Gupta
  • 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:3
  • 期号:12
  • 页码:224-228
  • 出版社:Association of Computer Communication Education for National Triumph (ACCENT)
  • 摘要:The growth of internet technology spread a large amount of data communication. The communication of data compromised network threats and security issues. The network threats and security issues raised a problem of data integrity and loss of data. For the purpose of data integrity and loss of data before 20 year Anderson developed a model of intrusion detection system. Initially intrusion detection system work on process of satirical frequency of audit system logs. Latter on this system improved by various researchers and apply some other approach such as data mining technique, neural network and expert system. Now in current research trend of intrusion detection system used soft computing approach such as fuzzy logic, genetic algorithm and machine learning. In this paper discuss some method of data mining and soft computing for the purpose of intrusion detection. Here used KDDCUP99 dataset used for performance evaluation for this technique.
  • 关键词:IDS; Data Mining; soft computing; KDDCUP99.
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