• DocumentCode
    2529642
  • Title

    Feature Omission Vulnerabilities: Thwarting Signature Generation for Polymorphic Worms

  • Author

    Gundy, Matthew Van ; Chen, Hao ; Su, Zhendong ; Vigna, Giovanni

  • Author_Institution
    Univ. of California, Davis
  • fYear
    2007
  • fDate
    10-14 Dec. 2007
  • Firstpage
    74
  • Lastpage
    85
  • Abstract
    To combat the rapid infection rate of today´s Internet worms, signatures for novel worms must be generated soon after an outbreak. This is especially critical in the case of polymorphic worms, whose binary representation changes frequently during the infection process. In this paper, we examine the assumptions underlying two leading network-based signature generation systems for polymorphic worms: polygraph [14] and Hamsa [12]. By identifying an assumption of both systems not met by all vulnerabilities, we discover a class of vulnerabilities (feature omission vulnerabilities) that neither system can accurately characterize. We demonstrate the limitations of polygraph and Hamsa by testing the signatures that they generate for exploits targeting a feature omission vulnerability. We discuss why feature omission vulnerabilities are difficult to characterize and how increased semantic awareness can help the signature generation process.
  • Keywords
    digital signatures; program testing; Hamsa; Internet worms; Polygraph; binary representation; feature omission vulnerabilities; infection process; network-based signature generation systems; polymorphic worms; signature generation thwarting; Application software; Bayesian methods; Character generation; Computer security; Computer worms; Filtering; Internet; Telecommunication traffic; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Security Applications Conference, 2007. ACSAC 2007. Twenty-Third Annual
  • Conference_Location
    Miami Beach, FL
  • ISSN
    1063-9527
  • Print_ISBN
    978-0-7695-3060-4
  • Type

    conf

  • DOI
    10.1109/ACSAC.2007.42
  • Filename
    4412978