Identifying statistically anomalous regions in time series of network traffic
Article No.: 67, Pages 1 - 2
Abstract
Traffic anomalies are specific types of events and conditions which differ from the normal or expected network behavior, and therefore should be brought to the attention of network operators. Examples of such events include, but are not limited to link or router outages, Denial-of-Service (DoS) attacks, flash crowds, port scans and misconfigured devices.
References
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P. Barford, J. Kline, D. Plonka, and A. Ron. A signal analysis of network traffic anomalies. In Proceedings of the ACM IMW, pages 71--82, 2002.
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A. K. Jain, M. N. Murty, and P. J. Flynn. Data clustering: a review. ACM Computing Surveys, 31(3):264--323, 1999.
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A. Lakhina, M. Crovella, and C. Diot. Mining anomalies using traffic feature distributions. In Proceedings of the ACM SIGCOMM, pages 217--228, August 2005.
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A. Soule, K. Salamatian, and N. Taft. Combining filtering and statistical methods for anomaly detection. In Proceedings of the ACM IMC, pages 331--344, 2005.
- Identifying statistically anomalous regions in time series of network traffic
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December 2007
448 pages
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- Alcatel-Lucent
- SIGCOMM: ACM Special Interest Group on Data Communication
- Thomson
- CISCO
- IMDEA
- IBM: IBM
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Association for Computing Machinery
New York, NY, United States
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Published: 10 December 2007
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