• DocumentCode
    1822286
  • Title

    Research on Intrusion Detection Based on an Improved SOM Neural Network

  • Author

    Jiang, Dianbo ; Yang, Yahui ; Xia, Min

  • Author_Institution
    Sch. of Software & Microelectron., Peking Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-20 Aug. 2009
  • Firstpage
    400
  • Lastpage
    403
  • Abstract
    Neural networks approach is an advanced methodology used for intrusion detection. As a type of neural network, Self-organizing Maps (SOM) is getting more attention in the field of intrusion detection. In this paper, some improvements on SOM algorithm are made in order to increase detection rate and improve the stability of intrusion detection, include: (1) Modify the strategy of ldquowinner-take-allrdquo to decrease underutilized or completely unutilized neurons. (2) Introduce interaction weight which describes the effect between each neuron in the output layer to enhance the relationships between the input pattern and the weights of all the nodes when adjusting weights; The improved SOM is implemented and applied to the intrusion detection. The validities and feasibilities of the improved SOM are confirmed through experiments on KDD Cup 99 datasets. The experiment result shows that the detection rate has been increased by employing the improved SOM.
  • Keywords
    neural nets; security of data; intrusion detection; neural network; self-organizing maps; Biological neural networks; Computer networks; Internet; Intrusion detection; Neural networks; Neurons; Protection; Self organizing feature maps; Stability; Supervised learning; Improved SOM; Intrusion Detection; Self-organizing Maps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-0-7695-3744-3
  • Type

    conf

  • DOI
    10.1109/IAS.2009.247
  • Filename
    5284114