Anomaly detection of network traffic based on wavelet packet

Gao Jun, Hu Guangmin, Yao Xingmiao, Kow Chuen Chang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

27 Citations (Scopus)


The rapid and accurate detection of network traffic anomaly is one of the preconditions to guarantee the effective work of the network. Aiming at the deficiency of present methods of network traffic anomaly detection, we propose a scale-adaptive method based on wavelet packet. By means of wavelet packet decomposition, our method can adjust the decomposition process adaptively, has the same detective ability to the anomaly of various frequency, especially the middle and high frequency ones which can not be checked out by the multi-resolution analysis. By means of adaptive reconstruction of the wavelet packet coefficient of different wavelet domains which anomaly, our method is able to confirm the characteristics of anomaly and enhance the reliability of detection. The simulation results prove that the method can detect the network traffic anomaly efficiently.
Original languageEnglish
Title of host publication2006 Asia-Pacific Conference on Communications, APCC
Publication statusPublished - 1 Dec 2006
Event2006 Asia-Pacific Conference on Communications, APCC - Busan, Korea, Republic of
Duration: 31 Aug 20061 Sept 2006


Conference2006 Asia-Pacific Conference on Communications, APCC
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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