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An Approach to Early Computer Network Intrusion Detection Based on the Wavelet Transform Energy Spectra Analysis

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Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23) (IITI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 777))

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Abstract

The current stage of development of cybersecurity has led to the need to create new and improve old methods of data analysis. The paper proposes a novel approach to early intrusion detection based on the analysis of the spectral plane of the signal and the detail coefficients obtained by wavelet transform. The approach makes it possible to consider data not only in the frequency domain, but also in the time domain, which greatly simplifies the localization of anomalies. Wavelet analysis can effectively extract information from a signal and is suitable for anomaly detection, while energy spectrum analysis allows you to determine the physical nature of this signal and implement its suppression or filtering. The approach represents the signal at different frequency values. Different wavelets have several decomposition levels, and each level has a different center frequency. The energy spectrum of the signal was reconstructed from the wavelet coefficients. For a given energy spectrum, the energy cumulate at high, medium and low frequencies was calculated. Experimental results have shown that this approach is well suited for detecting anomalies in network traffic and can be applied to detect new attacks.

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Acknowledgements

The research was supported by the grant of the Russian Science Foundation No. 23-11-20024, https://rscf.ru/en/project/23-11-20024/, and Saint-Petersburg Science Foundation.

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Authors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS), 14th Line, 39, St. Petersburg, 199178, Russia

    Igor Saenko & Peter Bortniker

  2. Admiral Makarov State University of Maritime and Inland Shipping, 5/7, Dvinskaya st., Saint-Petersburg, 198035, Russia

    Oleg Lauta

  3. Saint-Petersburg Signal Academy, 3, Tihoretsky prospekt, Saint-Petersburg, 194064, Russia

    Inna Zhdanova & Nikita Vasiliev

Authors
  1. Igor Saenko
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  2. Peter Bortniker
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  3. Oleg Lauta
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  4. Inna Zhdanova
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  5. Nikita Vasiliev
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Corresponding author

Correspondence to Igor Saenko .

Editor information

Editors and Affiliations

  1. Rostov State Transport University, Rostov-on-Don, Russia

    Sergey Kovalev

  2. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Igor Kotenko

  3. Rostov State Transport University, Rostov-on-Don, Russia

    Andrey Sukhanov

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Saenko, I., Bortniker, P., Lauta, O., Zhdanova, I., Vasiliev, N. (2023). An Approach to Early Computer Network Intrusion Detection Based on the Wavelet Transform Energy Spectra Analysis. In: Kovalev, S., Kotenko, I., Sukhanov, A. (eds) Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23). IITI 2023. Lecture Notes in Networks and Systems, vol 777. Springer, Cham. https://doi.org/10.1007/978-3-031-43792-2_7

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