• DocumentCode
    1935694
  • Title

    A Survivability Quantitative Analysis Model for Network System Based on Attack Graph

  • Author

    Zhang, Le-Jun ; Wang, Wei ; Guo, Lin ; Yang, Wu ; Yang, Yong-Tian

  • Author_Institution
    Harbin Eng. Univ., Harbin
  • Volume
    6
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    3211
  • Lastpage
    3216
  • Abstract
    Survivability is the ability of a system to continue operating despite the presence of abnormal events such as intrusions. Ensuring system survivability has increased in importance as critical infrastructures have become heavily dependent on computers. In this paper we present a survivability quantitative analysis model for network system based on attack graph, which indicates that survivability depends on network system itself, as well as the environment where it´s running. We identify the intrusion scenarios via attack graph analysis, and then suggest a quantitative measure of network system survivability. Mathematics formulas are given and network nodes that influenced survivability are investigated. From a case study, we identify the compromisable nodes that can be penetrated and damaged by intrusion and provide valuable suggestions to enhance system survivability design. The model is not only suitable for simple network systems but also applicable to distributed ones as long as the system is divided into atomic components.
  • Keywords
    graph theory; security of data; attack graph analysis; critical infrastructures; network system survivability; survivability quantitative analysis model; Automation; Cybernetics; Electronic mail; Finance; Information analysis; Information security; Machine learning; Mathematics; Power system modeling; Telecommunication computing; Attack graph; Quantitative analysis; Survivability model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370701
  • Filename
    4370701