Paper Title:
An Continuous Wavelet Transform-Based Detection Approach to Traffic Anomalies
  Abstract

Anomalous traffic often has a significant impact on network activities and lead to the severe damage to our networks because they usually are involved with network faults and network attacks. How to detect effectively network traffic anomalies is a challenge for network operators and researchers. This paper proposes a novel method for detecting traffic anomalies in a network, based on continuous wavelet transform. Firstly, continuous wavelet transforms are performed for network traffic in several scales. We then use multi-scale analysis theory to extract traffic characteristics. And these characteristics in different scales are further analyzed and an appropriate detection threshold can be obtained. Consequently, we can make the exact anomaly detection. Simulation results show that our approach is effective and feasible.

  Info
Periodical
Edited by
Han Zhao
Pages
2098-2102
DOI
10.4028/www.scientific.net/AMM.130-134.2098
Citation
D. D. Jiang, C. Yao, Z. Z. Xu, P. Zhang, Z. Yuan, W. D. Qin, "An Continuous Wavelet Transform-Based Detection Approach to Traffic Anomalies", Applied Mechanics and Materials, Vols. 130-134, pp. 2098-2102, 2012
Online since
October 2011
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