The article describes the approach based on the Bayesian networks for construction of probabilistic scenarios to simulate extreme situations in the energy sector. The paper proves the feasibility of using Bayesian networks to simulate energy security threats caused by the implementation of cyber threats. The main components of the scenario and their interrelations are described. The main stages of modeling extreme situations in the energy sector are determined. The position of the scenario approach in the main stages of identifying critical objects in the case of energy is recognized.
- L.V. Massel, A.G. Massel. “Semantic technologies based on the integration of Ontological, Cognitive and Event modelling”, III International Science and Technology Conference “OSTIS2013” Minsk, 2013, pp. 247-250 (in Russian).
- M. Rybnicek, R. Poisel, M. Ruzicka and S. Tjoa, “A Generic Approach to Critical Infrastructure Modeling and Simulation”, International Conference on Cyber Security “CyberSecurity” Alexandria, VA, USA, 2012, pp. 144-151.
- L. Barannik, S. Klementev, “Organization of critical infrastructure security in the U.S.”. No. 8. Foreign Military Review, 200, p. 3 (in Russian).
- V.I. Rabchuk, S.M. Senderov, G.B. Slavin, “Energy Security in Russia: Problems and Solutions”, Novosibirsk: ESI SB RAS, p. 197, 2011 (in Russian).
- A. Kondratev “The current trends in research of Critical Infrastructure in foreign countries”. No. 1. Foreign Military Review, 2012, pp 19-30 (in Russian).
- S. Sridhar, A. Hanh, M. Govindarasu, “Cyber-physical system security for the electric power grid”. Vol. 100. No. 1. Proc. IEEE, 2012, pp. 210-224.
- L.V. Massel, A.G. Massel, “Cyber security of Russia’s energy infrastructure as a component of national security,” 6th International Conference on Liberalization and Modernization of Power Systems, 2015, pp. 66-72.
- V.V. Mohor, A.M. Bogdanov, A.S. Kilevoj, “Information Technology. Methods of security. Сybersecurity manual (ISO/IES 27032:2012),” Three-K Kiev, 2013, p. 129, (in Russian).
- N.А. Mahutov, N.V. Аbrosimov, M.M. Gadenin, “Provision of safety - the priority in the sphere of fundamental and applied research”. No. 3. “Economic and Social Changes: Facts, Trends, Forecast”, 2013, pp. 39-61 (in Russian).
- N.I. Pyatkova, V.I. Rabchuk, S.M. Senderov, M.B. Cheltsov, “Energy Security in Russia: Problems and Solutions”, Novosibirsk: SB RAS, 2011, p. 211 (in Russian).
- L.V. Massel, N.I. Voropai, S.M. Senderov, A.G. Massel, “Cyber Danger as one of the strategic threats to energy security,” Cybersecurity issues, No. 4 (17), 2016, pp. 2-10 (in Russian).
- Positive Research 2017. Collection of research on practical safety. 2017. Available at: https://www.ptsecurity.com/upload/corporate/ruru/analytics/Positive-Research-2017-rus.pdf (accessed 07.07.2018). (in Russian)
- “WannaCry in industrial networks: work on mistakes”, Report of Kaspersky Lab, 2017. Available at: https://icscert.kaspersky.ru/reports/2017/06/08/wannacry-in-industrialnetworks/ (accessed 07.07.2018). (in Russian).
- A.G. Massel, D.A. Gaskova, “Application of risk-based approach to identify critical facilities in the energy sector with regard to cyber threats”, Proceedings of the 19th International Workshop оn Computer Science and Information Technologies. Germany, Baden-Baden. Publisher Ufa: USATU, Vol. 1, 2017, pp. 159-163.
- K.А. Feofanov, “Scenario capabilities of modern forecasting and management”, Vestnik MSTU “Stankin”, No. 4, 2009, pp. 126-132 (in Russian).
- V.V. Kulba, V.L Schultz, А.B Shelkov, “Information management. Part 2: Scenario approach”, National Security / Nota Bene, No. 4, 2009, pp. 4-15 (in Russian).
- D. Heckerman, “A Tutorial on Learning with Bayesian Networks”, Technical Report MSR-TR-95-06, Microsoft Research, March, 1995, p. 57.
- L.V. Massel, E.V. Pyatkova, “Application of Bayesian Networks for the intelligent support of Energy Security problem researches”, Proceedings of Irkutsk State Technical University, No. 2, 2012, pp. 8-13 (in Russian).
- L.V. Massel, A.G. Massel, “Technologies and tools for intelligent support of decision-making in extreme situations in energy”, Computational Technologies, Vol. 18, No. S1, 2013, pp. 37-44.