Anomaly Detections in Internet traffic using Empirical Measures
A. S. Syed Navaz1, S. Gopalakrishnan2, R. Meena3
1A. S. Syed Navaz, Asst. Professor, Department of Computer Applications, Periyar University/ Muthayammal College of Arts & Science/ Namakkal, India.
2S. Gopalakrishnan, Asst. Professor, Department of Computer Science, Periyar University/ Muthayammal College of Arts & Science/ Namakkal, India.
3R. Meena, Asst.Professor, Department of Computer Applications, Periyar University/ Muthayammal College of Arts & Science/ Namakkal, India.
Manuscript received on 07 February 2013 | Revised Manuscript received on 21 February 2013 | Manuscript Published on 28 February 2013 | PP: 58-61 | Volume-2 Issue-3, February 2013 | Retrieval Number: C0421022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Introducing Internet traffic anomaly detection mechanism based on large deviations results for empirical measures. Using past traffic traces we characterize network traffic during various time-of-day intervals, assuming that it is anomaly-free. Throughout, we compare the two approaches presenting their advantages and disadvantages to identify and classify temporal network anomalies. We also demonstrate how our framework can be used to monitor traffic from multiple network elements in order to identify both spatial and temporal anomalies. We validate our techniques by analyzing real traffic traces with time-stamped anomalies.
Keywords: Server, Client, Network, Anomaly Detection
Scope of the Article: Internet Computing