• DocumentCode
    2416756
  • Title

    Empirical and statistical analysis of risk analysis-driven techniques for threat management

  • Author

    Buyens, Koen ; Win, Bart De ; Joosen, Wouter

  • Author_Institution
    Dept. of Comput. Sci., KU Leuven
  • fYear
    2007
  • fDate
    10-13 April 2007
  • Firstpage
    1034
  • Lastpage
    1041
  • Abstract
    One of the challenges of secure software construction (and maintenance) is to get control over the multitude of threats in order to focus mitigation efforts on the most relevant ones. Risk analysis is one class of techniques for achieving threat reduction, but few studies are available that evaluate the quality of these techniques. In this paper, a selected set of risk analysis techniques have been evaluated and compared based on a realistic case study. The foundations for this analysis were threefold: we defined a set of high-level criteria, we compared the results of the different methods and we used statistical analysis techniques for studying additional characteristics. This analysis was performed on an independently developed case study of a significant size. For this experiment, the benefits of applying of these methods were limited for the categorization and the reduction of threats. Therefore, we also suggest ways to improve or complement these methods
  • Keywords
    risk analysis; security of data; software maintenance; statistical analysis; risk analysis; software construction; software maintenance; software security; statistical analysis; threat management; threat reduction; Computer science; Control system analysis; Control systems; Costs; Information processing; Performance analysis; Risk analysis; Risk management; Software maintenance; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Availability, Reliability and Security, 2007. ARES 2007. The Second International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    0-7695-2775-2
  • Type

    conf

  • DOI
    10.1109/ARES.2007.78
  • Filename
    4159906