• DocumentCode
    2845331
  • Title

    Network security situation quantitative evaluation based on the classification of attacks in attack-defense confrontation environment

  • Author

    Shuping, Yao ; Yingyan, Gu

  • Author_Institution
    Lab. of Comput. Network Defense Technol., Beijing Inst. of Technol., Beijing, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    6014
  • Lastpage
    6019
  • Abstract
    In order to remedy defects of the current network security evaluation systems, a novel evaluation algorithm, called quantitative network security situation evaluation based on the classification of attacks, is presented. Using this method, the traditional risk assessment is combined with network environment factors such as the network running status, asset security characteristic etc., and several quantitative indexes are extracted based on the analysis of factors which can affect the LAN´s security situation. Then, evaluations are done based on the classification of attacks. Experiment results show that the novel method can provide situation information which is more objective and detailed so the security administrator can understand the LAN´s security situation more clearly.
  • Keywords
    local area networks; risk management; security of data; LAN security situation; asset security characteristic; attack-defense confrontation environment; evaluation algorithm; network environment factor; network security situation quantitative evaluation; risk assessment; security administrator; Automation; Computer networks; Computer security; Data mining; Data security; Information security; Laboratories; Network topology; Risk analysis; Risk management; Attack-defense Confrontation; Network Security; Situation Evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5195279
  • Filename
    5195279