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Multiresolution anomaly detection method for fractional Gaussian noise

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  • Lingsong Zhang
  • Zhengyuan Zhu
  • J. S. Marron

Abstract

Driven by network intrusion detection, we propose a MultiResolution Anomaly Detection (MRAD) method, which effectively utilizes the multiscale properties of Internet features and network anomalies. In this paper, several theoretical properties of the MRAD method are explored. A major new result is the mathematical formulation of the notion that a two-scaled MRAD method has larger power than the average power of the detection method based on the given two scales. Test threshold is also developed. Comparisons between MRAD method and other classical outlier detectors in time series are reported as well.

Suggested Citation

  • Lingsong Zhang & Zhengyuan Zhu & J. S. Marron, 2014. "Multiresolution anomaly detection method for fractional Gaussian noise," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(4), pages 769-784, April.
    • Handle: RePEc:taf:japsta:v:41:y:2014:i:4:p:769-784
    DOI: 10.1080/02664763.2013.850065
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    References listed on IDEAS

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    1. Irene Gijbels & Peter Hall & Aloïs Kneip, 1999. "On the Estimation of Jump Points in Smooth Curves," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(2), pages 231-251, June.
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    Cited by:

    1. Lasse Holmström & Leena Pasanen, 2017. "Statistical Scale Space Methods," International Statistical Review, International Statistical Institute, vol. 85(1), pages 1-30, April.

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