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A New Network Anomaly Detection Technique Based on Per-Flow and Per-Service Statistics

  • Yuji Waizumi
  • Daisuke Kudo
  • Nei Kato
  • Yoshiaki Nemoto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3802)

Abstract

In the present network security management, improvements in the performances of Intrusion Detection Systems(IDSs) are strongly desired. In this paper, we propose a network anomaly detection technique which can learn a state of network traffic based on per-flow and per-service statistics. These statistics consist of service request frequency, characteristics of a flow and code histogram of payloads. In this technique, we achieve an effective definition of the network state by observing the network traffic according to service. Moreover, we conduct a set of experiments to evaluate the performance of the proposed scheme and compare with those of other techniques.

Keywords

Intrusion Detection Anomaly Detection Intrusion Detection System Anomaly Score Network Intrusion Detection System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yuji Waizumi
    • 1
  • Daisuke Kudo
    • 2
  • Nei Kato
    • 1
  • Yoshiaki Nemoto
    • 1
  1. 1.Graduate School of Information Sciences(GSIS)Tohoku UniversitySendai, MiyagiJapan
  2. 2.DAI NIPPON PRINTING CO., LTD.TokyoJapan

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