• DocumentCode
    3452412
  • Title

    Anomaly detection using call stack information

  • Author

    Feng, Henry Hanping ; Kolesnikov, Oleg M. ; Fogla, Prahlad ; Lee, Wenke ; Gong, Weibo

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Massachusetts, Amherst, MA, USA
  • fYear
    2003
  • fDate
    11-14 May 2003
  • Firstpage
    62
  • Lastpage
    75
  • Abstract
    The call stack of a program execution can be a very good information source for intrusion detection. There is no prior work on dynamically extracting information from the call stack and effectively using it to detect exploits. In this paper we propose a new method to do anomaly detection using call stack information. The basic idea is to extract return addresses from the call stack, and generate an abstract execution path between two program execution points. Experiments show that our method can detect some attacks that cannot be detected by other approaches, while its convergence and false positive performance is comparable to or better than the other approaches. We compare our method with other approaches by analyzing their underlying principles and thus achieve a better characterization of their performance, in particular on what and why attacks will be missed by the various approaches.
  • Keywords
    invasive software; program diagnostics; abstract execution path; anomaly detection; attacks; call stack information; convergence; extract return addresses; false positive performance; intrusion detection; program execution; program execution points; Automata; Automatic generation control; Computerized monitoring; Convergence; Counting circuits; Data mining; Educational institutions; Intrusion detection; Performance analysis; Runtime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Security and Privacy, 2003. Proceedings. 2003 Symposium on
  • ISSN
    1081-6011
  • Print_ISBN
    0-7695-1940-7
  • Type

    conf

  • DOI
    10.1109/SECPRI.2003.1199328
  • Filename
    1199328