• DocumentCode
    2250154
  • Title

    Incremental intrusion detecting method based on SOM/RBF

  • Author

    Tian, Li-ye ; Liu, Wei-peng

  • Author_Institution
    Dept. of Electron. & Inf. Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
  • Volume
    6
  • fYear
    2010
  • fDate
    11-14 July 2010
  • Firstpage
    2849
  • Lastpage
    2853
  • Abstract
    An incremental intrusion detecting model is proposed in this paper. This model integrates unsupervised Self Organizing Map and supervised Radial Basis Function to complete incremental learning. Self Organizing Map can get new type intrusion information and generate new nodes in Radial Basis Function. By this model, intrusion of unknown type can be detected online. Experiment results show our model could detect new type intrusions without forgetting the old ones.
  • Keywords
    learning (artificial intelligence); radial basis function networks; security of data; self-organising feature maps; RBF; SOM; incremental intrusion detection; incremental learning; supervised radial basis function; unsupervised self organizing map; Artificial neural networks; Cybernetics; Intrusion detection; Machine learning; Neurons; Tin; Training; Artificial neural network; Intrusion detection system; RBF; SOM; incremental learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4244-6526-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2010.5580770
  • Filename
    5580770