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Evaluating the Functioning Quality of Data Transmission Networks in the Context of Cyberattacks

Author

Listed:
  • Andrey Privalov

    (Electrical Communication Department, Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia)

  • Igor Kotenko

    (Saint-Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS) 39, 14 Liniya, 199178 St. Petersburg, Russia)

  • Igor Saenko

    (Saint-Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS) 39, 14 Liniya, 199178 St. Petersburg, Russia)

  • Natalya Evglevskaya

    (St. Petersburg Signal Academy, 3 Tikhoretsky Ave., 194064 St. Petersburg, Russia)

  • Daniil Titov

    (Electrical Communication Department, Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia)

Abstract

Cyberattacks against the elements of technological data transmission networks represent a rather significant threat of disrupting the management of regional electric power complexes. Therefore, evaluating the functioning quality of data transmission networks in the context of cyberattacks is an important task that helps to make the right decisions on the telecommunication support of electric power systems. The known models and methods for solving this problem have limited application areas determined by the admissible packet distribution laws. The paper proposes a new method for evaluating the quality of the functioning of data transmission networks, based on modeling the process of functioning of data transmission networks in the form of a stochastic network. The proposed method removes restrictions on the form of the initial distributions and makes the assumptions about the exponential distribution of the expected time and packet servicing in modern technological data transmission networks unnecessary. The method gives the possibility to evaluate the quality of the network functioning in the context of cyberattacks for stationary Poisson transmission and self-similar traffic, represented by Pareto and Weibul flows models. The obtained evaluation results are in good agreement with the data represented in previously published papers.

Suggested Citation

  • Andrey Privalov & Igor Kotenko & Igor Saenko & Natalya Evglevskaya & Daniil Titov, 2021. "Evaluating the Functioning Quality of Data Transmission Networks in the Context of Cyberattacks," Energies, MDPI, vol. 14(16), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4755-:d:608681
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    References listed on IDEAS

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    1. Guang-Qian Peng & Guangtao Xue & Yi-Chao Chen, 2018. "Network Measurement and Performance Analysis at Server Side," Future Internet, MDPI, vol. 10(7), pages 1-18, July.
    2. Igor Kotenko & Igor Saenko & Oleg Lauta & Aleksander Kribel, 2020. "An Approach to Detecting Cyber Attacks against Smart Power Grids Based on the Analysis of Network Traffic Self-Similarity," Energies, MDPI, vol. 13(19), pages 1-24, September.
    3. Nelson, Richard Graham & Azaron, Amir & Aref, Samin, 2016. "The use of a GERT based method to model concurrent product development processes," European Journal of Operational Research, Elsevier, vol. 250(2), pages 566-578.
    4. Andrey Privalov & Vera Lukicheva & Igor Kotenko & Igor Saenko, 2020. "Increasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering," Energies, MDPI, vol. 13(11), pages 1-18, June.
    5. Zhaoyang Qu & Yunchang Dong & Nan Qu & Lei Wang & Yang Li & Yu Zhang & Sylvere Mugemanyi, 2019. "Survivability Evaluation Method for Cascading Failure of Electric Cyber Physical System Considering Load Optimal Allocation," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-15, July.
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    Cited by:

    1. Paul Cristian Andrei & Horia Andrei, 2022. "Power Systems’ Connectivity and Resiliency: Modeling, Simulation and Analysis," Energies, MDPI, vol. 15(8), pages 1-3, April.

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