Multiresolution anomaly detection method for fractional Gaussian noise |
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| Authors: | Lingsong Zhang Zhengyuan Zhu J. S. Marron |
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| Affiliation: | 1. Department of Statistics, Purdue University, 150 N. University St., West Lafayette, IN 47907, USA;2. Department of Statistics &3. Statistical Laboratory, Snedecor Hall, Iowa State University, Ames, IA 50011, USA;4. Operations Research, University of North Carolina, CB3260, Chapel Hill, NC 27599, USA |
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| 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. |
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| Keywords: | fractional Gaussian noise long range dependence multiscale method outlier detection time series |
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