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

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. Copyright 2006 John Wiley & Sons, Ltd.

authors

• Reddy, Narasimha

published proceedings

• QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL

author list (cited authors)

• Kwon, D. W., Ko, K., Vannucci, M., Reddy, A., & Kim, S.

citation count

• 22

complete list of authors

• Kwon, DW||Ko, K||Vannucci, M||Reddy, ALN||Kim, S

publication date

• December 2006

publisher

• Wiley  Publisher

published in

• Quality and Reliability Engineering International  Journal

keywords

• Change Point Detection
• Network Traffic
• Statistical Hypothesis Testing
• Wavelet Transforms

Digital Object Identifier (DOI)

• 10.1002/qre.781

start page

• 953

end page

• 969

volume

• 22

issue

• 8

URL

• http://dx.doi.org/10.1002/qre.781