Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection is a thorough exploration of mathematical models and tools that are designed to strengthen critical infrastructures against threats – both natural and adversarial. Divided into two volumes, this first volume examines stochastic modeling across key economic sectors and their interconnections, while the second volume focuses on advanced mathematical methods for enhancing infrastructure protection.
The book covers a range of themes, including risk assessment techniques that account for systemic interdependencies within modern technospheres, the dynamics of uncertainty, instability and system vulnerabilities. The book also presents other topics such as cryptographic information protection and Shannon's theory of secret systems, alongside solutions arising from optimization, game theory and machine learning approaches.
Featuring research from international collaborations, this book covers both theory and applications, offering vital insights for advanced risk management curricula. It is intended not only for researchers, but also educators and professionals in infrastructure protection and stochastic optimization.
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Alexei A. Gaivoronski is Professor at the Norwegian University of Science and Technology, Norway. His research focuses on risk theory, and its applications in finance, energy, telecommunications and stochastic optimization.
Pavel S. Knopov is Head of Department at V.M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine. His research focuses on statistical decision theory, stochastic optimal control and stochastic optimization.
Vladimir I. Norkin is Leading Researcher at V.M. Glushkov Institute of Cybernetics, Ukraine. His research focuses on operations research.
Volodymyr A. Zaslavskyi is Professor at the Taras Shevchenko National University of Kyiv, Ukraine. His research focuses on systems analysis, risk and the reliability of critical systems.
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