• DocumentCode
    2571494
  • Title

    Polymorphic Worm Detection Using Signatures Based on Neighborhood Relation

  • Author

    Wang, Jie ; Wang, Jianxin ; Sheng, Yu ; Chen, Jianer

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
  • fYear
    2009
  • fDate
    25-27 June 2009
  • Firstpage
    347
  • Lastpage
    353
  • Abstract
    In recent years, worm signatures suffer from difficulties to detect polymorphic worms because these worms can change their patterns dynamically. In this paper, a class of neighborhood-relation signatures (NRS) are proposed, including 1-NRS, 2-NRS and (1,2)-NRS. NRS can be used for detecting polymorphic worms since these worms often remain the same relationship between bytes in changing their patterns. Two signature generation algorithm based on expectation-maximization (EM) and Gibbs Sampling are designed to generate NRS. We perform extensive experiments to demonstrate the effectiveness of NRS and the correctness of the process of signatures generation. Experiment results show that our approach of defending polymorphic worm based on NRS is more effective than other approach based on existed signatures.
  • Keywords
    digital signatures; expectation-maximisation algorithm; invasive software; sampling methods; Gibbs sampling algorithm; NRS; expectation-maximization algorithm; neighborhood-relation signature; polymorphic worm detection; signature generation algorithm; Atherosclerosis; Change detection algorithms; Cryptography; Frequency; High performance computing; Information science; Internet; Intrusion detection; Payloads; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing and Communications, 2009. HPCC '09. 11th IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-4600-1
  • Electronic_ISBN
    978-0-7695-3738-2
  • Type

    conf

  • DOI
    10.1109/HPCC.2009.59
  • Filename
    5167013