• DocumentCode
    3330017
  • Title

    Application protocols identification using Non-parametric Estimation method

  • Author

    Guang-Lu Sun ; Fei Lang ; Mingming Yang ; Jing Hua

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Harbin Univ. of Sci. & Technol., Harbin, China
  • Volume
    2
  • fYear
    2011
  • fDate
    22-24 Aug. 2011
  • Firstpage
    765
  • Lastpage
    768
  • Abstract
    Application protocols identification (APPI) is of fundamental importance to many network tasks. Traditional payload-based methods are difficult to identify new encrypted protocols. Many machine learning methods cannot achieve high performance. In this paper, we address an identification method based on Bayesian theory and Non-parametric Estimation which has good performance in the field of pattern recognition. The new method firstly abstracts the statistical features from the payloads of the flows. Then application protocols are identified with Non-parametric Estimation method. Experimental results show that the new method achieves over 80% in F-score for protocols identification.
  • Keywords
    Bayes methods; computer network security; cryptographic protocols; parameter estimation; pattern recognition; Bayesian theory; F-score; application protocols identification; encrypted protocols; nonparametric estimation method; pattern recognition; payload-based methods; Bayesian methods; Computational modeling; Educational institutions; Estimation; Payloads; Protocols; Training; feature template; non-parametric estimation; traffic identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Strategic Technology (IFOST), 2011 6th International Forum on
  • Conference_Location
    Harbin, Heilongjiang
  • Print_ISBN
    978-1-4577-0398-0
  • Type

    conf

  • DOI
    10.1109/IFOST.2011.6021134
  • Filename
    6021134