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Traffic Abnormalities Identification Based on the Stationary Parameters Estimation and Wavelet Function Detailization

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Mathematical Modeling and Simulation of Systems (MODS 2019)

Abstract

The article deals with the analysis of the of corporate network traffic properties using statistical methods. The complex method of estimating the stationary of computer network traffic using the autocorrelation function and the Hurst index is proposed. To detect the abnormal behavior of computer network traffic, the wavelet analysis method using the Fourier function, has been developed and tested.

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Acknowledgment

This research is funded by the NATO SPS Project CyRADARS (Cyber Rapid Analysis for Defense Awareness of Real-time Situation), Project SPS G5286.

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Correspondence to Igor Skiter .

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Stoianov, N., Lytvynov, V., Skiter, I., Lytvyn, S. (2020). Traffic Abnormalities Identification Based on the Stationary Parameters Estimation and Wavelet Function Detailization. In: Palagin, A., Anisimov, A., Morozov, A., Shkarlet, S. (eds) Mathematical Modeling and Simulation of Systems. MODS 2019. Advances in Intelligent Systems and Computing, vol 1019. Springer, Cham. https://doi.org/10.1007/978-3-030-25741-5_9

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