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Detection of Distributed Denial of Service Attacks in Large-Scale Networks Based on Methods of Mathematical Statistics and Artificial Intelligence

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Abstract

It is proposed to use the mathematical apparatus of wavelet transforms combined with the clustering of the obtained and transformed coefficients to detect attacks in the traffic of backbone networks. The wavelet transform coefficients obtained from the parameters of network packets are checked for the degree of multiple dependence, on the basis of which the standard deviation is calculated and the resulting coefficients are clustered to identify anomalies of the investigated network flow. The efficiency of the proposed method is confirmed by the results of experiments on detecting denial of service attacks.

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Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, 195251, St. Petersburg, Russia

    I. V. Alekseev

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  1. I. V. Alekseev
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Correspondence to I. V. Alekseev.

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Translated by M. Chubarova

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Alekseev, I.V. Detection of Distributed Denial of Service Attacks in Large-Scale Networks Based on Methods of Mathematical Statistics and Artificial Intelligence. Aut. Control Comp. Sci. 54, 952–957 (2020). https://doi.org/10.3103/S0146411620080052

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  • DOI: https://doi.org/10.3103/S0146411620080052

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