A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
IEEE Internet Computing
Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
The impact of residential broadband traffic on Japanese ISP backbones
ACM SIGCOMM Computer Communication Review
Mining anomalies using traffic feature distributions
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Analysis of internet backbone traffic and header anomalies observed
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Internet traffic classification demystified: myths, caveats, and the best practices
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
Packet-level traffic measurements from the Sprint IP backbone
IEEE Network: The Magazine of Global Internetworking
Active learning and subspace clustering for anomaly detection
Intelligent Data Analysis
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In a large backbone network, it is important to detect shape traffic fluctuation for servicing robust network. However, there are too many interfaces to monitor the characteristics of traffic. First we collect volume traffic of boundary link. From the volume traffic, we make groups which have similar traffic patterns by hierarchical clustering algorithm. This result shows that most of traffic has similar patterns, but some traffic which is far from centroid has an anomaly traffic pattern. This paper gives a hint for network operators that which traffic has to be checked out.