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Home - National Award, 2025 - Optimization of security risks for critical infrastructure

Optimization of security risks for critical infrastructure

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Work number - P 6 FILED

Presented V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine

Authors:
1. ATOEV Kostyantyn Leonovych – Candidate of Biological Sciences, Senior Researcher of the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine;
2. GORBACHUK Vasyl Mykhailovych – Doctor of Physical and Mathematical Sciences, Professor, Head of the Department of the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine;
3. DANILOV Valeriy Yakovych – Doctor of Technical Sciences, Professor, Professor of the Department of Artificial Intelligence of the Educational and Scientific Institute of Applied Systems Analysis of the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”;
4. KYRYLYUK Volodymyr Semenovich - Doctor of Physical and Mathematical Sciences, Leading Researcher of the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine;
5. KLYUSHYN Dmytro Anatoliyovych - Doctor of Physical and Mathematical Sciences, Professor, Professor of the Department of Computational Mathematics, Faculty of Computer Science and Cybernetics of Taras Shevchenko National University of Kyiv;
6. KOVALCHUK Lyudmila Vasylivna - Doctor of Technical Sciences, Professor, Leading Researcher of the G.E. Pukhov Institute of Modeling Problems in Energy of the NAS of Ukraine.
7. NORKIN Volodymyr Ivanovich - Doctor of Physical and Mathematical Sciences, Leading Researcher of the V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine;
8. SEMENOV Volodymyr Viktorovych - Doctor of Physical and Mathematical Sciences, Professor, Professor of the Department of Computational Mathematics, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv.

Ensuring reliable monitoring and security of critical infrastructure (CI) is a key problem of modern engineering and information technologies. The series of works developed a methodology for optimizing security risks for various CI sectors, based on mathematical modeling of risks and uncertainties.

A comprehensive approach to risk assessment is proposed, which includes the adaptation of statistical methods for cases with sufficient data samples and the application of mathematical modeling methods in conditions of uncertainty or distortion of information. All main CI sectors are considered, which allows assessing the cumulative effect of threats and taking into account exogenous and endogenous factors, including climate change and pandemics.

For the first time, existing risk assessment methods are systematized, which increases the accuracy of forecasts. Stochastic and hierarchical dynamic models are adapted for planning optimal resource allocation to protect CIs from terrorist attacks and catastrophic events. A risk assessment method based on catastrophe theory and dynamic models that take into account data scarcity is proposed.

A new class of polyhedral coherent risk measures is introduced to take into account risk when searching for optimal solutions under uncertainty. New methods for finding equilibrium decentralized solutions are proposed. Efficient algorithms for variational inequalities are developed, which are used to assess environmental risks, machine learning problems, and game models for CI protection.

New methods for assessing the stability of non-Markovian block ciphers, optimizing statistical tests for analyzing crypto primitives, and assessing the security of smart contracts in decentralized electricity markets are proposed.

The use of machine learning and artificial intelligence methods increases the efficiency of data analysis and risk management. In the field of acoustic sensing, echo signal processing algorithms are developed to improve measurement accuracy. In financial forecasting, adaptive models for identifying uncertainties were used, and in biometric verification, hybrid autoencoders were proposed, demonstrating increased resistance to changes in input data.

Number of publications: 2 individual monographs, 42 collective monographs (27 published abroad), 147 articles in category "A" journals (138 in foreign publications) and 98 articles in category "B" journals. The total number of references to the authors' publications/h-index for the work according to the databases is respectively: Web of Science 1189 / 15, Scopus 1773 / 20, Google Scholar 5516 / 30. 4 patents of Ukraine for a useful model, 2 certificates of copyright registration for a work, 1 national standard of Ukraine was implemented.

National Award, 2025

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