• DocumentCode
    2608826
  • Title

    Analysis of anomaly packet´s feature based on honeypot

  • Author

    Xinliang, Wang ; Fang, Liu ; Luying, Chen ; Zhenming, Lei

  • Author_Institution
    Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2009
  • fDate
    18-20 Oct. 2009
  • Firstpage
    271
  • Lastpage
    275
  • Abstract
    The deep study of anomaly feature based on the particular server was made in this paper. By continuously monitoring on the honeypot deployed in Internet Data Center for more than two months, the experimental results were summarized and some initial exploratory models were built. The models show that the number of attackers for the main attack types and ports can be described by normal distribution; meanwhile, the average packet number that each attacker generates per day can be described by log-normal distribution. This research aims to contribute to endeavor in the wider security research community to build methods and obtain some statistical models, grounded on strong empirical work, for assessment of the robustness of systems in hostile environments, and the anomaly traffic sampling, detection and classification on the backbone.
  • Keywords
    Internet; computer centres; computer network management; log normal distribution; normal distribution; security of data; statistical analysis; Internet data center; anomaly traffic sampling; log-normal distribution; security research community; statistical model; Gaussian distribution; Internet; Log-normal distribution; Monitoring; Robustness; Sampling methods; Security; Spine; Traffic control; Web server; Anomaly detection; Anomaly feature; Heavy-tail; Honeypot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4590-5
  • Electronic_ISBN
    978-1-4244-4591-2
  • Type

    conf

  • DOI
    10.1109/ICBNMT.2009.5348493
  • Filename
    5348493