2. Home
  3. ARCHIVE
  4. 2018
  5. VOL 40, NO 2 (2018)
  6. Архив номеров
  7. 2019 год
  8. 41-2

Electronic modeling

Vol 41, No 2 (2019)

 

CONTENTS

Mathematical Modeling and Computation Methods

  VYNNYCHUK S.D., MISKO V.M.
Method of Multiple Polinomial k-Sieve with Using of Signal Reminders During Sieving of Probable Values
3-22
  DOROGYY Y.Y., DOROHA-IVANIUK O.O., FERENS D.A.
Resources Distribution Model of Critical IT Infrastructure with Clear Parameters Based on the Particle Swarm Algorithm
23-38

Computational Processes and Systems

  EFANOV D.V., SAPOZHNIKOV V.V., SAPOZHNIKOV Vl.V.
Modified Wieght-Bits and Weight-Transitions Sum Codes for Discrete Device Synthesis with Error Detection
39-62

Application of Modeling Methods and Facilities

  KUTSAN Yu.G., GURIEIEV V.O., LYSENKO Y.M., AVETISYAN O.V.
Cybersecurity in the Electric Power Systems of Ukraine
63-80
  KAMENEVA I.P., ARTEMCHUK V.O., IATSYSHYN A.V.
Probabilistic Modeling of Expert Knowledge Using Psychosemantics Methods (Using Environmental Data As An Example)
81-98
 
97-110
  BIDYUK P.I., HUSKOVA V.H.
Analysis of Solvency Using Data Mining Methods
111-120

Short Notes

  ZVARITCH V.M., DAVYDIUK A.V.
The Method of Color Formalization of the Level of Information Security Risk
121-126

METHOD OF MULTIPLE POLINOMIAL k-SIEVE WITH USING OF SIGNAL REMINDERS DURING SIEVING OF PROBABLE VALUES

S.D. Vynnychuk, V.M. Misko

Èlektron. model. 2018, 41(2):03-22
https://doi.org/10.15407/emodel.41.02.003

ABSTRACT

An algorithm for the method of a Multiple Quadratic k-Sieve (MQkS) is proposed, which is aAn algorithm for the method of a Multiple Quadratic k-Sieve (MQkS) is proposed, which is amodification of the quadratic sieve method (QS), in which, when sieving test values, it is proposedto perform a preliminary sieving on the basis of the comparison, the remainder yk(X) = X2 - kN (k ≥ 1) with signaling residuesy yk*(X), where yk*(X) is the product of the first powersof the factors yk(X). Among the test values, the ones for which log (yk*(X)) < h log (yk*(X)), where a real number h ∈ [0,1] is a parameter that can be selected. It is established that at growth N the value of h increases, at which the lowest value of the calculation time is reached. It is also establishedthat a decrease in the time of obtaining a sufficient number of B-smooth ones can be obtainedby limiting the parameters of powers of the B-smooth divisors exceeding the unit for a pluralityof elements of a common factor base, greater than a certain value, which is determined onthe basis of the value of the parameter kff. On the basis of numerical experiments with relativelysmall numbers of order 10m at m = 20÷32, it is shown that the time of calculating a sufficient numberof B-smooth is a function of the introduced parameter kff, with a monotonically increasing ratioof calculation timewith the value of the parameter kff = 1 (no restriction) to theminimumtime. Thesteps of the algorithm of the method and the ideas of their implementation are described. A heuristicestimation of the complexity of the MQkS method for a number of values of the parameter pla is given.

KEYWORDS

integer factoring, quadratic sieve, multiple sieve.

REFERENCES

1. Gorbenko, I.D., Dolgov, V.I., Potiy, A.V. and Fedorchenko, V.N. (1995), “Channel analysis of the RSA system vulnerability”, Bezopansost informasii, no. 2, pp. 22-26.
2. Brown Daniel, R.L. “Breaking RSA May Be As Difficult As Factoring”, available at: http://www.pgpru.com/novosti /2005/1026vzlomrsabezfaktorizaciirealennoneeffektiven.
3. Kannan, B. and Rajakani, M. (2018), “Algorithmic strategies for solving complex problems in cryptography. Advances in information security, privacy, and ethics (AISPE) book series”, IGI Global, Hershey, Pennsylvania, USA.
4. “Quadratic sieve”, available at: https://en.wikipedia.org/wiki/Quadratic_sieve.
5. Silverman, R.D (1987), “The multiple polynomial quadratic sieve”, Math. Comp, Vol. 48 (177), pp. 329-339.
https://doi.org/10.1090/S0025-5718-1987-0866119-8
6. Vynnychuk, S.D. and Misko, V.M. (2018), “Method of multiple quadratic k-sieve integer factorization”, Elektron. modelirovanie, Vol. 40, no. 5, pp. 3-26, available at: 
https://doi.org/10.15407/emodel.40.05.003
7. Vasilenko, O.N. (2003), Teoretiko-chislovyie algoritmy v kriptografii [Number-Theoretic Algorithms in Cryptography], MTsNMO, Moscow, Russia.
8. Ishmukhametov, Sh.T. (2011), Metody faktorizatsii naturalnykh chisel [Methods of natural numbers factorization], Kasanskiy Universitet, Kasan, Russia.
9. Landquist, E. (2001), “The Quadratic Sieve Factoring Algorithm”, MATH: Cryptographic Algorithms, no. 488, pp. 1-11.
10. Vynnychuck, S. and Misko, V. (2018), “Acceleration analysis of the quadratic sieve method based on the online matrix solving”, Eastern-European Journal of Eenterprise Technologies / Mathematics and cybernetics, Vol. 2, no. 4 (92), pp. 33-38, 
https://doi.org/10.15587/1729-4061.2018.127596

Full text: PDF

RESOURCES DISTRIBUTION MODEL OF CRITICAL IT INFRASTRUCTURE WITH CLEAR PARAMETERS BASED ON THE PARTICLE SWARM ALGORITHM

Y.Y. Dorogyy, O.O. Doroha-Ivaniuk, D.A. Ferens

Èlektron. model. 2018, 41(2):23-38
https://doi.org/10.15407/emodel.41.02.023

ABSTRACT

A detailed analysis of the methods and algorithms for allocating resources for virtualized IT infrastructuresA detailed analysis of the methods and algorithms for allocating resources for virtualized IT infrastructureshas been carried out. A detailed description of the mathematical model of resourceallocation of a critical IT infrastructure with clear parameters and its use in combination with theparticle swarm method is given. The method of particle swarm, the principle of finding the best solution and its basic operations for solving a given problem are disclosed. The last part of the articlesolution and its basic operations for solving a given problem are disclosed. The last part of the articlepresents experimental researches of the proposed model of distribution of critical IT infrastructureresources with clear parameters based on the particle swarm method.

KEYWORDS

architecture, resource allocation, particle swarm method, critical IT infrastructure.

REFERENCES

1. Globa, L.S., Skulish, M.A. and Dyadenko, O.M. (2007), Matematicheskie osnovy postroeniya informatsionno-telekommunikatsionnykh sistem [Mathematical Foundations of Construction of Information and Telecommunication Systems], Norita-plus, Kyiv, Ukraine.
2. Gorin, M. (2007), “Corporate Data Center: Beyond Technology”, Connect! Mir Svjazi, no. 8, pp. 19-20.
3. Kirillov, I. (2010), “Commercial data centers in Ukraine: a new stage of development”, Seti i biznes, no. 3, available at: http://www.sib.com.ua/arhiv 2010/2010_3/statia_3_1_2010/statia_3_1_2010.htm (accessed December 10, 2018).
4. Badger, L., Grance, T., Patt-Corner, R. and VoasCloud, J. (2012), “Computing Synopsis and Recommendations. Recommendations of the National Institute of Standards and Technology”, Special Publication.
https://doi.org/10.6028/NIST.SP.800-146
5. Bibershtein, N. and Bouz, S. (2007), Kompas v mire servis-orientirovannoy arhitektury [Compass in the world of service-oriented architecture], KUDITs-Press, Moscow, Russia.
6. Krafzik, D., Banke, K. and Slama, D. (2005), Enterprise SOA: Service-Oriented Architecture Best Practices, Prentice Hall Professional.
7. Kaur, R. and Kaur, A. (2014), “A Review Paper on Evolution of Cloud Computing, its Approaches and Comparison with Grid Computing”, International Journal of Computer Science and Information Technologies, Vol. 5, pp. 6060-6063.
8. Gupta, A., Sarood, O. and Kale, L.V. (2014), “Optimizing VM Placement for HPC in the Cloud”, International Letters of Social and Humanistic Sciences, Vol. 16, pp. 1-6.
9. Joseph, J. and Fellenstein, C. (2004), Grid Computing, Prentice Hall Professional.
10. Nabrzyski, J., Schopf, J.M. and Weglarz, J. (2004), Grid Resource Management: State of the Art and Future Trends, Springer.
https://doi.org/10.1007/978-1-4615-0509-9
11. Goldworm, B. and Skamarock, A. (2007), Blade servers and virtualization: transforming enterprise computing while cutting costs, Wiley Publishing, Inc.
12. Ruest, N. and Ruest, D. (2009), Virtualization, A Beginner’s Guide, McGraw Hill Professional.
13. Telenik, S.F., Rolik, O.I., Bukasov, M.M. and Labunskiy, A.Yu. (2009), “Virtual Machine Management Models for Server Virtualization”, Visnik NTUU «KPI»: Informatika, upravlennya ta obchislyuvalna tekhnika, no. 51, pp. 147-152.
14. Dorogyy, Ya.Yu., Doroga-Ivanyuk, O.O. and Ferens, D.A. (2018), “Critical IT infrastructure resource allocation model with clear parameters based on genetic algorithm”, Information technology and security, Vol. 6, no. 2(11), pp. 124-144.
https://doi.org/10.20535/2411-1031.2018.6.2.153497
15. Buyya, R., Broberg, J. and Goscinski, A.M. (2010), Cloud Computing: Principles and Paradigms, John Wiley & Sons.
https://doi.org/10.1002/9780470940105
16. Hu, X. and Eberhart, R.C. (2001), “Tracking dynamic systems with PSO: Where’s the cheese”, Proceedings of the Workshop on Particle Swarm Optimization, IN, pp. 80-83.
17. Shi, Y.H. and Eberhart, R. C. (1999), “Empirical study of particle swarm optimization”, Proceedings17. Shi, Y.H. and Eberhart, R. C. (1999), “Empirical study of particle swarm optimization”, Proceedingsof the Congress on Evolutionary Computation, Vol. 3, pp. 1945-1950.
https://doi.org/10.1109/CEC.1999.785511
18. Eberhart, R.C. and Shi, Y. (2001), “Tracking and optimizing dynamic systems with particleswarms”, Proceedings of the 2001 Congress on Evolutionary Computation, Vol. 1, pp. 94-100. DOI: https://doi.org/10.1109/CEC.2001.934376.
19. Carlisle, A. and Dozler, G. (2002), “Tracking changing extrema with adaptive particleswarm optimizer”, Proceedings of the 2002 Soft Computing, Multimedia Biomedicine, ImageProcessing and Financial Engineering, Orlando, FL, USA, pp. 265-270.
20. Du, W., and Li, B. (2008). “Multi-strategy ensemble particle swarm optimization for dynamicoptimization”, International Journal of Information Sciences, Vol. 178, no. 15, pp. 3096-3109. DOI:
https://doi.org/10.1016/j.ins.2008.01.020.
21. Tasgetiren, M.F., Sevkli, M., Liang, Y.-C. and Gencyilmaz, G. (2004), “Particle swarm optimizationalgorithm for permutation flow shop sequencing problem”, Proceedings of the 4thInternational Workshop on Ant Colony, Optimization, and Swarm Intelligence (ANTS2004),Brussels, Belgium, pp. 382-390.
https://doi.org/10.1007/978-3-540-28646-2_38
22. Tasgetiren, M.F., Sevkli, M., Liang, Y.-C. and Gencyilmaz, G. (2006), “Particle swarm optimizationalgorithm for single-machine total weighted tardiness problem”, Proceedings ofthe Congress on Evolutionary Computation, Vol. 2, pp. 1412-1419.
23. Van der Maaten, L.J.P. and Hinton, G.E. (2008), “Visualizing High-Dimensional Data Usingt-SNE”, Journal of Machine Learning Research, Vol. 9, pp. 2579-2605.

Full text: PDF

MODIFIED WIEGHT-BITS AND WEIGHT-TRANSITIONS SUM CODES FOR DISCRETE DEVICE SYNTHESIS WITH ERROR DETECTION

D.V. Efanov, V.V. Sapozhnikov, Vl.V. Sapozhnikov

Èlektron. model. 2018, 41(2):39-62
https://doi.org/10.15407/emodel.41.02.039

ABSTRACT

The authors analyzed the feature of detection ability in data vectors by modified weight-bits andThe authors analyzed the feature of detection ability in data vectors by modified weight-bits andweight-transition sum codes, which were constructed using a sequence of weights that form a naturalseries of numbers. The article presents the conditions for constructing a family of weightedcodes with the detection of any single error in data vectors of a given length m. The key characteristicsof weighted sum code are determined, which determine the conditions for their use in buildingreliable logic devices. A classification of weighted sum codes with weight coefficients from anatural series of numbers has been developed.

KEYWORDS

testable systems, sum code, Berger code, weighted codes with summation, codetestable systems, sum code, Berger code, weighted codes with summation, codeproperties, data vector, undetectable error.

REFERENCES

1. Sapozhnikov, V.V., Sapozhnikov, Vl.V., Khristov, H.A. and Gavzov, D.V. (1995), Metody1. Sapozhnikov, V.V., Sapozhnikov, Vl.V., Khristov, H.A. and Gavzov, D.V. (1995), Metodypostroeniya bezopasnykh mikroelektronnykh sistem zheleznodorozhnoy avtomatiki [Methodsfor constructing safety microelectronic systems for railway automation], Transport,Moscow, Russia.
2. Fujiwara, E. (2006), Code Design for Dependable Systems: Theory and Practical Applications,John Wiley & Sons, New Jersey, USA.
https://doi.org/10.1002/0471792748
3. Ubar, R., Raik, J. and Vierhaus, H.T. (2011), Design and Test Technology for DependableSystems-on-Chip, IGI Global, Hershey, New York, USA.
https://doi.org/10.4018/978-1-60960-212-3
4. Drozd, A.V., Kharchenko, V.S. and Antoshchuk, S.G. (2012), Rabochee diagnostirovaniebezopasnykh informatsionno-upravlyayuschikh sistem [Objects and Methods of On-LineTesting for Safe Instrumentation and Control Systems], National Aerospace University,Kharkov, Ukraine.
5. Berger, J.M. (1961), “A Note on Error Detection Codes for Asymmetric Channels”, Informationand Control, Vol. 4, no. 1, pp. 68-73. DOI:
https://doi.org/10.1016/S0019-9958(61)80037-5.
6. Busaba, F.Y. and Lala, P.K. (1994), “Self-Checking Combinational Circuit Design for Singleand Unidirectional Multibit Errors”, Journal of Electronic Testing: Theory and Applications,no. 1, pp. 19-28. DOI: https://doi.org/10.1007/BF00971960.
7. Matrosova, A.Yu., Levin, I. and Ostanin, S.A. (2000), “Self-Checking Synchronous FSMNetwork Design with Low Overhead”, VLSI Design, Vol. 11, no. 1, pp. 47-58. DOI:
https://doi.org/10.1155/2000/46578.
8. Ostanin, S. (2017), “Self-Checking Synchronous FSM Network Design for Path DelayFaults”, Proceedings of the 15th IEEE East-West Design & Test Symposium(EWDTS`2017), Novi Sad, Serbia, September 29-October 2, 2017, pp. 696-699. DOI:
https://doi.org/10.1109/EWDTS.2017.8110129.
9. Saposhnikov, V.V., Morosov, A., Saposhnikov, Vl.V. and Göessel, M. (1998), “A New DesignMethod for Self-Checking Unidirectional Combinational Circuits”, Journal of ElectronicTesting: Theory and Applications, Vol. 12, no. 1-2, pp. 41-53. DOI:
https://doi.org/10.1023/A:1008257118423.
10. Göessel, M., Ocheretny, V., Sogomonyan, E. and Marienfeld, D. (2008), New Methods ofConcurrent Checking, Springer Science+Business Media, Nederland.
11. Nicolaidis, M. and Zorian, Y. (1998), “On-Line Testing for VLSI – A Compendium of Approaches”,Journal of Electronic Testing: Theory and Applications, no. 12, pp. 7-20. DOI:
https://doi.org/10.1023/A:1008244815697.
12. Mitra, S. and McCluskey, E.J. (2000), “Which Concurrent Error Detection Scheme toÑhoose?”, Proceeding of the International Test Conference, USA, Atlantic City, October03-05, 2000, pp. 985-994. DOI: https://doi.org/10.1109/TEST.2000.894311.
13. Sogomonyan, E.S. and Slabakov, E.V. (1989), Samoproveryaemye ustroystva i otkazoustoychivyesistemy [Self-checking devices and failover systems], Radio i svyaz, Moscow, USSR.
14. Piestrak, S.J. (1995), Design of Self-Testing Checkers for Unidirectional Error DetectingCodes, Wroclaw Polytechnic University, Wroclaw, Poland.
15. Ghosh, S., Basu, S. and Touba, N.A. (2005), “Synthesis of Low Power CED Circuits Basedon Parity Codes”, Proceeding of the 23rd IEEE VLSI Test Symposium (VTS’05), 2005, pp.315-320.
https://doi.org/10.1109/VTS.2005.80
16. Kubalík, P. and Kubatova, H. (2005), “Parity Codes Used for On-Line Testing in FPGA”,Acta Polytechnika, Vol. 45, no. 6, pp. 53-59.
17. Aksyonova, G.P. (2008), “On Functional Diagnosis of Discrete Devices Under Imperfect Data Processing Conditions”, Problemy upravleniya, no. 5, pp. 62-66.
18. Sapozhnikov, V., Sapozhnikov, Vl. and Efanov, D. (2015), “Modular Sum Code in BuildingTestable Discrete Systems”, Proceeding of the 13th IEEE East-West Design & Test Symposium(EWDTS`2015), Batumi, Georgia, September 26-29, 2015, pp. 181-187. DOI:
https://doi.org/10.1109/EWDTS.2015.7493133.
19. Efanov, D.V., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2015), “Applications of ModularSummation Codes to Concurrent Error Detection Systems for Combinational BooleanCircuits”, Avtomatika i telemekhanika, no. 10, pp. 152-169.
https://doi.org/10.1134/S0005117915100112
20. Das, D. and Touba, N.A. (1999), “Synthesis of Circuits with Low-Cost Concurrent Error DetectionBased on Bose-Lin Codes”, Journal of Electronic Testing: Theory and Applications,Vol. 15, no. 1-2, pp. 145-155. DOI: https://doi.org/10.1023/A:1008344603814.
21. Cherepanova, M.R. (2016), “A study into influence of sum code module value on structureredundancy of concurrent error detection systems”, Izv. Peterburgskogo un-ta putey soobscheniya,no. 2, pp. 279-288.
https://doi.org/10.20295/1815-588X-2016-2-179-188
22. Blyudov, A.A., Efanov, D.V., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2012), “Formationof the Berger Modified Code with Minimum Number of Undetectable Errors of DataBits”, Elektronnoe modelirovanie, Vol. 34, no. 6, pp. 17-29.
23. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Efanov, D.V. (2017), “Effective method ofmodifying code with on-bits summation”, Izv. vuzov. Priborostroenie, Vol. 60, no. 11, pp.1020-1032. DOI:
https://doi.org/10.17586/0021-3454-2017-60-11-1020-1032.
24. Blyudov, A.A., Efanov, D.V., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2014), “OnCodes with Summation of Data Bits in Concurrent Error Detection Systems”, Avtomatika itelemekhanika, no. 8, pp. 131-145.
https://doi.org/10.1134/S0005117914080098
25. Berger, J.M. (1961), “A Note on Burst Detection Sum Codes”, Information and Control,Vol. 4, no. 2-3, pp. 297-299, DOI: 10.1016/S0019-9958(61)80024-7.26. Das, D. and Touba, N.A. (1999), “Weight-Based Codes and Their Application to ConcurrentError Detection of Multilevel Circuits”, Proceeding of the 17th IEEE VLSI Test Symposium,USA, CA, Dana Point, April 25-29, 1999, pp. 370-376.
https://doi.org/10.1016/S0019-9958(61)80024-7
27. Das, D., Touba, N.A., Seuring, M. and Gossel, M. (2000), “Low Cost Concurrent Error DetectionBased on Modulo Weight-Based Codes”, Proceeding of the IEEE 6th InternationalOn-Line Testing Workshop (IOLTW), Spain, Palma de Mallorca, July 3-5, 2000, pp. 171-176. DOI:
https://doi.org/10.1109/OLT.2000.856633.
28. Saposhnikov, V. and Saposhnikov, Vl. (1999), “New Code for Fault Detection in Logic Circuits”,Proceeding of the 4th International Conference on Unconventional Electromechanicaland Electrical Systems, St. PÂ, Russia, June 21-24, 1999, pp. 693-696.
29. Mehov, V., Saposhnikov, V., Sapozhnikov, Vl. and Urganskov, D. (2007), “Concurrent ErrorDetection Based on New Code with Modulo Weighted Transitions between InformationBits”, Proceedings of the 7th IEEE East-West Design & Test Workshop (EWDTW`2007),Erevan, Armenia, September 25-30, 2007, pp. 21-26.
30. Mekhov, V.B., Sapozhnikov, V.V. and Sapozhnikov, Vl.V. (2008), “Checking of CombinationalCircuits Basing on Modification Sum Codes”, Avtomatika i telemekhanika, no. 8,pp. 153-165.
https://doi.org/10.1134/S0005117908080134
31. Dmitriev, V.V. (2015), “On the two weighing methods and their influence on properties ofsum codes of weighted transitions in functional logical scheme control systems”, Izv.Peterburgskogo un-ta putey soobscheniya, no. 3, pp. 119-129.
32. Sapozhnikov, V.V., Sapozhnikov, Vl.V., Efanov, D.V. and Kotenko, A.G. (2017), “ModuloCodes with Summation of Weighted Transitions with Natural Number Sequence of Weights”,Trudy SPIIRAN, no. 1, pp. 137-164. DOI:
https://doi.org/10.15622/sp.50.6.
33. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Efanov, D.V. (2017), “Modulo weighted codeswith summation with minimum number of undetectable errors in data vectors”, Elektron.modelirovanie, Vol. 39, no. 4, pp. 69-88.
https://doi.org/10.15407/emodel.39.04.069
34. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Efanov, D.V. (2017), “Codes with Summation34. Sapozhnikov, V.V., Sapozhnikov, Vl.V. and Efanov, D.V. (2017), “Codes with Summationwith a Sequence of Weight Coefficients, Forming a Natural Series of Numbers, in ConcurrentError Detection Systems”, Elektron. modelirovanie, Vol. 39, no. 5, pp. 37-58.
https://doi.org/10.15407/emodel.39.05.037
35. Efanov, D., Sapozhnikov, V. and Sapozhnikov, Vl. (2017), “The Synthesis of Self-CheckingCombinational Devices Based on Properties of Codes With Summation of Weighted Transitionsand Selection of Testable Outputs Groups”, Proceeding of the 15th IEEE East-WestDesign & Test Symposium (EWDTS`2017), Novi Sad, Serbia, September 29-October 2,2017, pp. 671-677. DOI:
https://doi.org/10.1109/EWDTS.2017.8110075.
36. Efanov, D., Sapozhnikov, V. and Sapozhnikov, Vl. (2017), “Modified codes with weightedtransitionssummation in concurrent error detection systems of combinational circuits”,Trudy In-ta sistemnogo programmirovaniya RAN, Vol. 29, no. 5, pp. 39-60. DOI:
https://doi.org/10.15514/ISPRAS-2017-29(5)-3.

Full text: PDF

CYBERSECURITY IN THE ELECTRIC POWER SYSTEMS OF UKRAINE

Yu.G. Kutsan, V.O. Gurieiev, Y.M. Lysenko, O.V. Avetisyan

Èlektron. model. 2018, 41(2):63-80
https://doi.org/10.15407/emodel.41.02.063

ABSTRACT

The functional structure of electric power systems (EPS) to assess the most reliable places ofThe functional structure of electric power systems (EPS) to assess the most reliable places ofunauthorized impact on the work of critical infrastructure is analyzed in the article. It is imperativeto take into account the continuous operation in time and a very complex hierarchicalsystem of management of EÇS facilities and the United Electric Power System (ECO),which consists of a large number of often not directly interconnected automatic (without humanparticipation) and automated systems (with human participation in solutions) managementof generation units (nuclear, thermal, solar, wind and hydroelectric power plants),power transmission networks (transportation) and electricity consumption. The variants ofcyber threats of these very systems and objects of the existing EÇS management structure arealso the subject of research of this work. It is proposed to develop operational preventivemethods aimed at identifying and preventing the conditions for the emergence of cyberthreats in the energy sector.

KEYWORDS

cyber threats, power system modes, mode simulation, electronic training,cyber threats, power system modes, mode simulation, electronic training,scenarios of anti-cybernetic training.

REFERENCES

1. (2016), “Understanding Cybercrime: A Guide for Developing Countries”, available at:1. (2016), “Understanding Cybercrime: A Guide for Developing Countries”, available at:http://www.itu.int/dms_pub/itu-d/oth/01/0B/D010B0000073301PDFR.pdf (accessed April2017).
2. Kobets, B.B. and Volkova, I.O. (2010), Innovatsionnoe razvitie elektroenergetiki na bazekontseptsii Smart Grid [Innovative development of electroenergy on the base of conceptionof Smart Grid], IATs Energiya, Moscow, Russia.
3. Starovoytov, A.V. (2011), «Cybersecurity as an urgent problem of our time», Informatcij i svyaz, no. 6, pp. 4-7.
4. Borodakii, Y.V., Dobrodeev, A.V. and Butusov, I.V. (2014), “Cybersecurity as the mainfactor of national and international security of the XXI century”, Voprosy kiberbezopasnosti,no. 1(2), pp. 5-12.
5. Markov, G.A. (2015), “Physical Security Issues”, Voprosy kiberbezopasnosti, no. 4 (12),pp. 70-76.
6. (2018), “ENTSO-E finalized the agreement on the accession of the ECO of Ukraine to thecontinental network of Europe”, available at: http://reform.energy/news/entso-e-finalizirovalosoglashenie-o-prisoedinenii-oes-ukrainy-k-kontinentalnoy-seti-evropy-1125 (accessed April2018).
7. Levinshtein, M.L. and Scherbachev, O.V. (1962), “The method of calculating the static stabilityof complex electrical systems using equivalent regulatory effects of stations andloads”, Izv. vuzov. Energetika, no. 8, pp. 11-19.
8. Tsukernik, L.V. and Korobchuk, K.V. (1969), “Calculation with the help of digital computersof the limit of static stability of a complex power system”, Dokl. na II Vsesoyuz.nauch.-tehn. sovesch. po ustoychivosti i nadezhnosti energosistem SSSR [Report on the IIAll-Union. scientific and technical meeting on stability and reliability of the power systemsof the USSR], Energiya, Moscow, Russia, pp. 56-62.
9. Gotman, V.I. and Gotman, O.V. (2006), “Equivalenting of energy bonding subsystemsbased on operational parameters”, Izv. vuzov. Elektomekhanika, no. 3, pp. 111-114.
10. Stroev, V.A. and Sulzhenko, C.V. (1997), Matematicheskoe modelirovanie elementov elektricheskikhsistem [Mathematical modeling of elements of electrical systems], MEI, Moscow,Russia.
11. Venikov, V.A. and Sukhanov, O.A. (1982), Kiberneticheskie modeli elektricheskikh sistem [Cybernetic models of electrical systems], Energoizdat, Moscow, Russia.
12. Gureev, V.O. (2018), “Development of algorithms and programs of high-speed methods forcalculating the operating modes of large electric power systems and power units for simulators”,Naukovi Pratsi VNTU, no. 1, pp. 1-5.
13. Kutsan, Y.G., Gureev, V.O. and Lysenko, E.M. (2018), “Modeling and developing an adaptiveautomated system for constructing emergency accident scenarios”, Elektronne modelyuvannya,no. 4, pp. 55-64. DOI:https://doi.org/10.15407/emodel.40.04.055.
14. Gureev, V.O. (2018), “Modeling great power systems for the development of computerizedtraining systems in energy systems”, Modelyuvannya ta informatsiini tekhnologii. Zbirnyknauk. prats IPME im. G.E. Pukhova, Vol. 83, pp. 94-105.
15. Gissinger, S., Chaumes, P., Antoine, J.-P. and Bihain, A. (2000), “An Advanced DispatcherTraining Simulator”, Computer Applications in Power, Vol. 13, no. 2, pp. 25-30.
https://doi.org/10.1109/67.831425
16. Karlsson, D., Hill, D. J. (1994), “Modeling and identification of nonlinear dynamic loads inpower systems”, IEEE Transactions on Power Systems, Vol. 9, no. 1, no. 157-166.
https://doi.org/10.1109/59.317546

Full text: PDF