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Anomaly Detection of Excessive Network Traffic Based on Ratio and Volume Analysis

  • Conference paper
Intelligence and Security Informatics (ISI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3975))

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Abstract

Recent attacks typically cause not only traffic congestion but also network failure exhausting network bandwidth, router processing capacity using the abnormal traffic or excessive network traffic, so that they can have an extremely large impact on the public network. Therefore we propose the detection mechanism of network traffic anomalies. This mechanism analyzes flow data based on the statistical anomaly detection, which supports the two analysis method- ratio based analysis and volume based analysis and correlates the results from these two models.

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References

  1. Barford, P., Kline, J., et al.: A Signal Analysis of Network Traffic Anomalies. In: Proceedings of ACM SIGCOMM Internet Measurement Workshop, France (November 2002)

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  2. Lee, S.H., Kim, H.J., Na, J.C., et al.: Abnormal Traffic Detection and Its Implementation. In: ICACT 2005, February 21-23 (2005)

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  3. Kim, S.S., Narasimha Reddy, A.L., Vannucci, M.: Detecting Traffic Anomalies at the Source through aggregate analysis of packet header data. In: TAMU-ECE-2003-03 (2003)

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Author information

Authors and Affiliations

  1. Network Security Department, Electronics and Telecommunications Research Institute, 161 Gajeong-Dong, Yuseong-Gu, Daejeon, 305-350, Korea

    Hyun Joo Kim, Jung C. Na & Jong S. Jang

Authors
  1. Hyun Joo Kim
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  2. Jung C. Na
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  3. Jong S. Jang
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Editor information

Editors and Affiliations

  1. School of Information and Computer Science, University of California, Irvine

    Sharad Mehrotra

  2. MIS Department, University of Arizona, 85721, Tucson, AZ, USA

    Daniel D. Zeng

  3. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  4. University of Texas at Dallas,  

    Bhavani Thuraisingham

  5. Chinese Academy of Sciences, 100190, Beijing, China

    Fei-Yue Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, H.J., Na, J.C., Jang, J.S. (2006). Anomaly Detection of Excessive Network Traffic Based on Ratio and Volume Analysis. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, FY. (eds) Intelligence and Security Informatics. ISI 2006. Lecture Notes in Computer Science, vol 3975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760146_107

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  • DOI: https://doi.org/10.1007/11760146_107

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34478-0

  • Online ISBN: 978-3-540-34479-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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