• DocumentCode
    1619987
  • Title

    ISMCS: An intelligent instruction sequence based malware categorization system

  • Author

    Huang, Kai ; Ye, Yanfang ; Jiang, Qinshan

  • Author_Institution
    Software Sch., Xiamen Univ., Xiamen, China
  • fYear
    2009
  • Firstpage
    509
  • Lastpage
    512
  • Abstract
    Recently, automated malware (e.g., viruses, backdoors, spyware, Trojans and worms) categorization methods and an industry-wide naming convention have been the computer security topics that are of great interest. Resting on the analysis of function based instruction sequence, we develop an intelligent instruction sequence based malware categorization system (ISMCS) using a novel weighted subspace clustering method. ISMCS is an integrated system consisting of three major modules: feature exactor, malware categorizer using weighted subspace clustering method and malware signature generator. ISMCS can not only effectively categorize malwares to different families, but also automatically generate the unify signature for every family. Promising experimental results demonstrate that the effectiveness of our ISMCS system outperform other existing malware categorization methods, such as K-Means and hierarchical clustering algorithms.
  • Keywords
    category theory; invasive software; ISMCS; automated malware; computer security; instruction sequence based malware categorization system; Clustering algorithms; Clustering methods; Computer industry; Computer science; Computer security; Computer viruses; Computer worms; Data mining; Frequency; Software systems; instruction sequence; malware categorization; weighted subspace clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Anti-counterfeiting, Security, and Identification in Communication, 2009. ASID 2009. 3rd International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-3883-9
  • Electronic_ISBN
    978-1-4244-3884-6
  • Type

    conf

  • DOI
    10.1109/ICASID.2009.5276989
  • Filename
    5276989