• DocumentCode
    1958157
  • Title

    Self-Adaptation Metrics for Active Cybersecurity

  • Author

    Musliner, David J. ; Friedman, Scott E. ; Marble, Tom ; Rye, Jeffrey M. ; Boldt, Michael W. ; Pelican, Michael

  • Author_Institution
    Smart Inf. Flow Technol., Minneapolis, MN, USA
  • fYear
    2013
  • fDate
    9-13 Sept. 2013
  • Firstpage
    53
  • Lastpage
    58
  • Abstract
    FUZZBUSTER is a host-based adaptive security system that automatically discovers, refines, and repairs vulnerabilities in hosted applications in order to prevent cyber attacks. FUZZBUSTER must decide when to adapt its applications, when to revoke its previous adaptations, and when to sacrifice functionality to improve security. This requires an adaptation quality metric that captures (1) an application´s susceptibility to cyber attacks and (2) an application´s functionality, since adapting an application affects both of these factors. FUZZBUSTER uses different types of test cases to measure security and functionality. In this paper, we describe FUZZBUSTER´s adaptation metrics and we present two different policies for balancing security and functionality. We provide empirical results comparing these policies, and we also demonstrate how FUZZBUSTER can temporarily sacrifice the functionality of hosted applications to increase host security, and then restore functionality when more favorable adaptations are found.
  • Keywords
    security of data; active cybersecurity; adaptation metrics; adaptation quality metric; adaptive security system; cyber attacks; fuzzbuster; hosted applications; self adaptation metrics; Computer crime; Conferences; Maintenance engineering; Measurement; Software; cybersecurity; fuzz-testing; self-adaptive immunity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptation and Self-Organizing Systems Workshops (SASOW), 2013 IEEE 7th International Conference on
  • Conference_Location
    Philadelphia, PA
  • Type

    conf

  • DOI
    10.1109/SASOW.2013.31
  • Filename
    6803258