• DocumentCode
    1690506
  • Title

    DDoS attack detection based on neural network

  • Author

    Li, Jin ; Liu, Yong ; Gu, Lin

  • Author_Institution
    Syst. Intell. Lab., Univ. of Aizu, Fukushima, Japan
  • fYear
    2010
  • Firstpage
    196
  • Lastpage
    199
  • Abstract
    DDoS attack is a major Internet security problem-DoS is that lots of clients simultaneously send service requests to certain server on the internet such that this server is too busy to provide normal services for others. Attackers using legitimate packets and often changing package information, so that traditional detection methods based on feature descriptions is difficult to detect it. This paper present an artificial intelligence DDoS attack detection method based on neural networks. In this method, analysis of server resources and network traffic, To training the ability of detection normal or abnormal, it have better results for detect DDoS attack.
  • Keywords
    Internet; artificial intelligence; computer network security; network servers; neural nets; packet switching; telecommunication traffic; DDoS attack detection; Internet security problem; artificial intelligence; legitimate packets; network traffic; neural network; package information; server resources; service requests; Accuracy; IP networks; Testing; Back Propagation Neural Network; Detection Rate; Distributed Denial of Service; False Negative; False Positive; LVQ Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aware Computing (ISAC), 2010 2nd International Symposium on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4244-8313-6
  • Type

    conf

  • DOI
    10.1109/ISAC.2010.5670479
  • Filename
    5670479