Anomaly identification based on flow analysis

The Quyent Le, Marat Zhanikeev, Yoshiaki Tanaka

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Citations (Scopus)

    Abstract

    Recently, the concern about network management and network security has inspired many research topics, among which, research on detecting and identifying anomalies has attracted a lot of interest. In this paper, we propose an anomaly identification method based on traffic flow analysis. The result of the research proves that by assembling some features of traffic flows and calculating some specific extended metrics, we can successfully detect and identify network anomalies with high accuracy. Besides, the method also proves its efficiency with the ability to quantify network anomalies and locate relevant network nodes. The research validity has been verified by both simulation data and real network data.

    Original languageEnglish
    Title of host publicationIEEE Region 10 Annual International Conference, Proceedings/TENCON
    DOIs
    Publication statusPublished - 2007
    Event2006 IEEE Region 10 Conference, TENCON 2006 - Hong Kong
    Duration: 2006 Nov 142006 Nov 17

    Other

    Other2006 IEEE Region 10 Conference, TENCON 2006
    CityHong Kong
    Period06/11/1406/11/17

      Fingerprint

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Le, T. Q., Zhanikeev, M., & Tanaka, Y. (2007). Anomaly identification based on flow analysis. In IEEE Region 10 Annual International Conference, Proceedings/TENCON [4142352] https://doi.org/10.1109/TENCON.2006.344124