• DocumentCode
    188175
  • Title

    Automated Intrusion Response System Algorithm with Danger Theory

  • Author

    Ling-Xi Peng ; Tian-Wei Chen

  • Author_Institution
    Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2014
  • fDate
    13-15 Oct. 2014
  • Firstpage
    31
  • Lastpage
    34
  • Abstract
    Intrusion response is a new generation of technology basing on active defence idea, which has very prominent significance on the protection of network security. However, the existing automatic intrusion response systems are difficult to judge the real "danger" of invasion or attack. In this study, an immune-inspired adaptive automated intrusion response system model, named as AIAIM, was given. With the descriptions of self, non-self, memory detector, mature detector and immature detector of the network transactions, the real-time network danger evaluation equations of host and network are built up. Then, the automated response polices are taken or adjusted according to the real-time danger and attack intensity, which not only solve the problem that the current automated response system models could not detect the true intrusions or attack actions, but also greatly reduce the response times and response costs. Theory analysis and experimental results prove that AIAIM provides a positive and active network security method, which will help to overcome the limitations of traditional passive network security system.
  • Keywords
    artificial immune systems; computer network security; adaptive automated intrusion response system; artificial immune system; danger theory; immature detector; memory detector; network security; real-time network danger evaluation equation; Communication networks; Detectors; Distributed computing; Knowledge discovery; Mathematical model; Real-time systems; Security; artificial immune; automated intrusion response system; danger evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2014 International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4799-6235-8
  • Type

    conf

  • DOI
    10.1109/CyberC.2014.16
  • Filename
    6984277