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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barford, P., Kline, J., et al.: A Signal Analysis of Network Traffic Anomalies. In: Proceedings of ACM SIGCOMM Internet Measurement Workshop, France (November 2002)
Lee, S.H., Kim, H.J., Na, J.C., et al.: Abnormal Traffic Detection and Its Implementation. In: ICACT 2005, February 21-23 (2005)
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)
Barford, P., Plonka, D.: Characteristics of network traffic flow anomalies. In: Proceedings of ACM SIGCOMM Internet Measurement Workshop, Francisco, CA (November 2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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)