Anomaly Detection and Localization by Diffusion Wavelet-based Analysis on Traffic Matrix

Teng Sun1, Hui Tian1 and Xuan Mei1

  1. Dept. of Electronics and Information Engineering
    Beijing Jiaotong University, Beijing, China
    htian@bjtu.edu.cn

Abstract

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.

Key words

traffic matrices, diffusion wavelets, multi-resolution analysis, anomaly detection

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS141001059S

Publication information

Volume 12, Issue 4 (November 2015)
Special Issue on Recent Advances in Information Processing, Parallel and Distributed Computing
Year of Publication: 2015
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Sun, T., Tian, H., Mei, X.: Anomaly Detection and Localization by Diffusion Wavelet-based Analysis on Traffic Matrix. Computer Science and Information Systems, Vol. 12, No. 4, 1361–1374. (2015)