Wavelet methods for the detection of anomalies and their application to network traffic analysis

D. W. Kwon, K. Ko, M. Vannucci, A. L.N. Reddy, S. Kim

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Here we develop an integrated tool for the online detection of network anomalies. We consider statistical change point detection algorithms, for both local changes in the variance and for the detection of jumps, and propose modified versions of these algorithms based on moving window techniques. We investigate performances on simulated data and on network traffic data with several superimposed attacks. All detection methods are based on wavelet packet transforms.

Original languageEnglish (US)
Pages (from-to)953-969
Number of pages17
JournalQuality and Reliability Engineering International
Volume22
Issue number8
DOIs
StatePublished - Dec 2006
Externally publishedYes

Keywords

  • Change point detection
  • Network traffic
  • Statistical hypothesis testing
  • Wavelet transforms

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

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