Flow traffic classification with support vector machine by using payload length

Masayoshi Kohara, Yoshiaki Hori, Kouichi Sakurai, Heejo Lee, Jae Cheol Ryou

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. In this paper, we propose flow traffic classification methods using support vector machine. Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. The proposals satisfy the following three requirements. Using to only flow information, not using port numbers, automatic making of traffic models. In this paper, we provide an empirical evaluation of our proposals using datasets of MIT Lincoln Laboratory, which illustrates that our proposals can classify network traffic flow over 90 % precision.

本文言語英語
ホスト出版物のタイトルProceedings of the 2009 2nd International Conference on Computer Science and Its Applications, CSA 2009
DOI
出版ステータス出版済み - 12 1 2009
イベント2009 2nd International Conference on Computer Science and Its Applications, CSA 2009 - Jeju Island, 大韓民国
継続期間: 12 10 200912 12 2009

その他

その他2009 2nd International Conference on Computer Science and Its Applications, CSA 2009
国/地域大韓民国
CityJeju Island
Period12/10/0912/12/09

All Science Journal Classification (ASJC) codes

  • 計算理論と計算数学
  • コンピュータ サイエンスの応用

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