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Diffusion wavelets (DW) transform has been successfully used in  Multi-Resolution Analysis (MRA) of traffic matrices because it inherently  adapts to the structure of the underlying network. There are many potential  applications based on DW analysis such as anomaly detection, routing  optimization and capacity plan, which, however, have not been well developed.  This paper shows how to apply two-dimensional DW transform in traffic matrix  analysis and anomaly detection. The experimental results demonstrate the  effectiveness of DW-based technique in traffic matrix analysis and anomaly  detection in practical networks. It also shows this new technique is  potential to be used in many other network applications.

Anomaly detection and localization by diffusion wavelet-based analysis on traffic matrix