• DocumentCode
    2756150
  • Title

    ShieldGen: Automatic Data Patch Generation for Unknown Vulnerabilities with Informed Probing

  • Author

    Cui, Weidong ; Peinado, Marcus ; Wang, Helen J. ; Locasto, Michael E.

  • Author_Institution
    Microsoft Res., Redmond, WA
  • fYear
    2007
  • fDate
    20-23 May 2007
  • Firstpage
    252
  • Lastpage
    266
  • Abstract
    In this paper, we present ShieldGen, a system for automatically generating a data patch or a vulnerability signature for an unknown vulnerability, given a zero-day attack instance. The key novelty in our work is that we leverage knowledge of the data format to generate new potential attack instances, which we call probes, and use a zero-day detector as an oracle to determine if an instance can still exploit the vulnerability; the feedback of the oracle guides our search for the vulnerability signature. We have implemented a ShieldGen prototype and experimented with three known vulnerabilities. The generated signatures have no false positives and a low rate of false negatives due to imperfect data format specifications and the sampling technique used in our probe generation. Overall, they are significantly more precise than the signatures generated by existing schemes. We have also conducted a detailed study of 25 vulnerabilities for which Microsoft has issued security bulletins between 2003 and 2006. We estimate that ShieldGen can produce high quality signatures for a large portion of those vulnerabilities and that the signatures are superior to the signatures generated by existing schemes.
  • Keywords
    digital signatures; ShieldGen; automatic data patch generation; data format specifications; informed probing; sampling technique; unknown vulnerabilities; vulnerability signature; zero-day attack instance; zero-day detector; Application software; Data analysis; Data security; Detectors; Filters; Probes; Protection; Protocols; Prototypes; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Security and Privacy, 2007. SP '07. IEEE Symposium on
  • Conference_Location
    Berkeley, CA
  • ISSN
    1081-6011
  • Print_ISBN
    0-7695-2848-1
  • Type

    conf

  • DOI
    10.1109/SP.2007.34
  • Filename
    4223230