• DocumentCode
    237696
  • Title

    Increasing performance Of intrusion detection system using neural network

  • Author

    Kumar, Sudhakar ; Yadav, Ankesh

  • Author_Institution
    Dept. of Electr. Eng., Nat. Inst. of Technol., Raipur, India
  • fYear
    2014
  • fDate
    8-10 May 2014
  • Firstpage
    546
  • Lastpage
    550
  • Abstract
    Rapid growth in Internet and in parallel attacks, vulnerability and threats, has made intrusion detection systems very essential component in all parts of security infrastructure. Building IDS is not a new task, classical signature based IDS are used but they are unable to handle novel attacks. In this paper artificial neural network based intrusion detection is proposed for complete KDD cup 99 dataset. Performance of the proposed ANN based IDS system is evaluated and results shows high anomaly detection accuracy for the complete KDD cup 99 dataset as compared to existing techniques.
  • Keywords
    neural nets; security of data; ANN based IDS system; Internet; artificial neural network based intrusion detection system; complete KDD cup 99 dataset; neural network; parallel attacks; security infrastructure; Accuracy; Artificial neural networks; Network topology; Probes; Servers; Spread spectrum communication; Topology; ANN; Intrusion Detection System; KDD99 dataset;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
  • Conference_Location
    Ramanathapuram
  • Print_ISBN
    978-1-4799-3913-8
  • Type

    conf

  • DOI
    10.1109/ICACCCT.2014.7019145
  • Filename
    7019145