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Adaptive Control System for Detecting Computer Attacks on Objects of Critical Information Infrastructure

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Abstract

This paper presents an adaptive control system for detecting computer attacks in CII based on a neuro-fuzzy analysis of variant cyber-threat spaces and parameters of the protected object using an adaptive neuro-fuzzy inference system (ANFIS) and the Takagi–Sugeno–Kang fuzzy basis. The results of experimental studies have shown that the developed system provides high accuracy and speed of detecting computer attacks in changing decision-making conditions.

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ACKNOWLEDGMENTS

Project results are achieved using the resources of supercomputer center of Peter the Great St.Petersburg Polytechnic University—SCC Polytechnichesky (http://www.spbstu.ru).

Funding

The research is funded by the Ministry of Science and Higher Education of the Russian Federation under the strategic academic leadership program “Priority 2030” (agreement 075-15-2021-1333 dated November 30, 2021).

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Authors and Affiliations

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

    V. M. Krundyshev & M. O. Kalinin

Authors
  1. V. M. Krundyshev
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  2. M. O. Kalinin
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Corresponding author

Correspondence to V. M. Krundyshev.

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The authors declare that they have no conflicts of interest.

Additional information

Translated by M. Chubarova

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Krundyshev, V.M., Kalinin, M.O. Adaptive Control System for Detecting Computer Attacks on Objects of Critical Information Infrastructure. Aut. Control Comp. Sci. 56, 1040–1048 (2022). https://doi.org/10.3103/S0146411622080090

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  • DOI: https://doi.org/10.3103/S0146411622080090

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