An Continuous Wavelet Transform-Based Detection Approach to Traffic Anomalies

Abstract:

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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 et al., "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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Price:

$35.00

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