• DocumentCode
    3213469
  • Title

    System and methodology for unknown Malware attack

  • Author

    Murugan, S. ; Kuppusamy, K.

  • Author_Institution
    ACTS Coordinator, Bangalore, India
  • fYear
    2011
  • fDate
    20-22 July 2011
  • Firstpage
    803
  • Lastpage
    804
  • Abstract
    Intrusion Detection Prevention Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection prevention are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection.
  • Keywords
    data mining; fuzzy logic; invasive software; neural nets; anomaly detection; artificial intelligence; data mining technique; fuzzy logic; host based detection; intrusion detection prevention system; misuse detection; network profiling; neural network; unknown malware attack; Data mining; Fuzzy Logic; Intrusion Detection; Network Security;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Sustainable Energy and Intelligent Systems (SEISCON 2011), International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1049/cp.2011.0475
  • Filename
    6143424