• DocumentCode
    519548
  • Title

    An intrusion detection method based on decision tree

  • Author

    Liu, Yongjin ; Li, Na ; Shi, Leina ; Li, Fangping

  • Author_Institution
    Sch. of Inf. Eng., Handan Coll., Handan, China
  • Volume
    1
  • fYear
    2010
  • fDate
    17-18 April 2010
  • Firstpage
    232
  • Lastpage
    235
  • Abstract
    How to find the intrusion behaviors is a problem that troubled the intrusion detection field for years. Until now, there is not a good method to solve it, epically in a realistic context. Most methods are effective on small data sets, but when used to the massive data of IDS, the effectiveness seems to be unsatisfactory. In this paper, a new method based on decision tree is discussed to solve the problem of low detection rate of massive data.
  • Keywords
    decision trees; security of data; decision tree; detection rate; intrusion behavior; intrusion detection method; massive data; Bagging; Boosting; Classification tree analysis; Decision trees; Ecosystems; Information systems; Intrusion detection; Large-scale systems; Stability; agent; decision tree; intrusion detection; random decision tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-5514-0
  • Type

    conf

  • DOI
    10.1109/EDT.2010.5496597
  • Filename
    5496597