DocumentCode :
2172944
Title :
Detecting low-rate periodic events in Internet traffic using renewal theory
Author :
McPherson, Sean ; Ortega, Antonio
Author_Institution :
Ming Hsieh Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
4336
Lastpage :
4339
Abstract :
In our previous work [1, 2] we studied detection of anomalies in packet arrival times for computer networks, most detection of denial of-service (DoS) attacks in Internet traffic. In this paper we reformulate the detection method proposed in [1] using renewal theory, providing several useful extensions. This reformulation also leads to a method that would be applicable to numerous real life signals that exist as discrete events, e.g., biological signals. Most importantly renewal theory allows us to characterize the performance of our detector and determine theoretical bounds on the time-to-detection. Compared to alternative methods that use frequency spectra or event arrival rates for detection our method is shown to be superior in terms of time-to-detection. Further, unlike rate based techniques, our method can estimate the multiple periods when multiple periodic anomalies occur simultaneously.
Keywords :
Internet; computer network security; telecommunication traffic; Internet traffic; biological signals; computer networks; denial of-service attacks; discrete events; event arrival rates; frequency spectra; low-rate periodic event detection; multiple periodic anomalies; renewal theory; time-to-detection; Approximation methods; Frequency domain analysis; Harmonic analysis; Histograms; Internet; Probability; Timing; Detection Algorithm; Discrete Event Systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5947313
Filename :
5947313
Link To Document :
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