• DocumentCode
    2373902
  • Title

    PDVDS: A Pattern-Driven Software Vulnerability Detection System

  • Author

    Cheng, Shaoyin ; Wang, Jinding ; Wang, Jiajie ; Yang, Jun ; Jiang, Fan

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2010
  • fDate
    11-13 Dec. 2010
  • Firstpage
    536
  • Lastpage
    541
  • Abstract
    The automatic detection of security vulnerabilities in binary program is challenging and lacks efficient tools. Current research and tools are mostly restricted to a specific platform and environment, which induces the trouble to detect all kinds of vulnerabilities with unified approach. Moreover, Existing methods need many manual operations and rely on the experience of researchers. This paper presents a cross-platform system for automatically software vulnerability detection based on uniform intermediate representation. It supports many platforms, including x86, PowerPC and ARM. The system lifts underlying instructions to intermediate representation from several platforms. Platform-independent analysis method is implemented based on intermediate representation by static analysis. It also uses a vulnerability pattern driver extracted from experience and knowledge to drive the automatic vulnerability detection during the analysis. The system called PDVDS has been realized. We have evaluated its effectiveness through validating many known vulnerabilities and detecting three zero-day vulnerabilities.
  • Keywords
    security of data; software reliability; ARM; PDVDS; PowerPC; binary program; cross-platform system; pattern-driven software vulnerability detection system; x86; pattern-driven; software analysis; static analysis; uniform intermediate representation; vulnerability detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Embedded and Ubiquitous Computing (EUC), 2010 IEEE/IFIP 8th International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-9719-5
  • Electronic_ISBN
    978-0-7695-4322-2
  • Type

    conf

  • DOI
    10.1109/EUC.2010.88
  • Filename
    5703573