Published December 30, 2022 | Version v1
Journal article Open

Development of an approach to the creation of an intellectual system of national security management

Creators

  • 1. Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine
  • 2. Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty
  • 3. Zhytomyr Military Institute named after S. P. Koroliov
  • 4. Taras Shevchenko National University of Kyiv

Description

The object of the research is intelligent systems for collecting, processing and analyzing information about the state of national security. Investigated problem: The problem that is solved in the research is the problem of building intelligent systems for collecting, processing and analyzing information about the state of national security with limitations on the available computing resources, reliability and given speed of processing of various types of data circulating in it. The main scientific results obtained during the study by the authors are: proposed approach to the development of intelligent systems for the collection, processing and analysis of information on the state of the state's national security. The proposed approach takes into account the security of the system, available forces and means, purpose, system effect, method of formation, resource composition, structure, management, the process of functioning according to the purpose, resource consumption and the specified efficiency criterion. This will allow to justify the requirements for software and hardware of intelligent systems for collecting, processing and analyzing information about the state of the state's national security. proposed architecture of intelligent systems for collecting, processing and analyzing information about the state of national security of the state. Its approximate composition, functional purpose and structure of the database management system are substantiated. The area of practical use of the research results: It is advisable to use the proposed scientific results when conducting research and development works on the creation of intelligent systems for collecting, processing and analyzing information about the state of national security of the state, and developing requirements for hardware and software of this type of systems. Field of application: software, information systems, decision support systems.

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References

  • Kuchuk, N., Mohammed, A. S., Shyshatskyi, A., Nalapko, O. (2019). The method of improving the efficiency of routes selection in networks of connection with the possibility of self-organization. International Journal of Advanced Trends in Computer Science and Engineering, 8 (1.2), 1–6.
  • Sova, O., Turinskyi, O., Shyshatskyi, A., Dudnyk, V., Zhyvotovskyi, R., Prokopenko, Y. et al. (2020). Development of an algorithm to train artificial neural networks for intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 1 (9 (103)), 46–55. doi: https://doi.org/10.15587/1729-4061.2020.192711
  • Makarenko, S. I., Mikhailov, R. L. (2013). Otcenka ustoichivosti seti sviazi v usloviiakh vozdeistviia na nee destabiliziruiushchikh faktorov. Radioengineering and Telecommunication Systems, 4, 69–79.
  • Bodyanskyy, E. V., Strukov, V. M., Uzlov, D. Yu. (2017). Generalizedmetrics in the problem of analysis of multidimensional data with different scales. Zbirnyk naukovykh prats Kharkivskoho natsionalnoho universytetu Povitrianykh Syl, 3 (52), 98–101
  • Semenov, V. V., Lebedev, I. S. (2019). Processing of signal information in problems of monitoring information security of unmanned autonomous objects. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 19 (3), 492–498. doi: https://doi.org/10.17586/2226-1494-2019-19-3-492-498
  • Zhou, S., Yin, Z., Wu, Z., Chen, Y., Zhao, N., Yang, Z. (2019). A robust modulation classification method using convolutional neural networks. EURASIP Journal on Advances in Signal Processing, 2019 (1). doi: https://doi.org/10.1186/s13634-019-0616-6
  • Shaheen, E. M., Samir, M. (2013). Jamming Impact on the Performance of MIMO Space Time Block Coding Systems over Multi-path Fading Channel. REV Journal on Electronics and Communications, 3 (1-2), 68–72. doi: https://doi.org/10.21553/rev-jec.56
  • Malik, S., Kumar, S. (2017). Optimized Phase Noise Compensation Technique using Neural Network. Indian Journal of Science and Technology, 10 (5), 1–6. doi: https://doi.org/10.17485/ijst/2017/v10i5/104348
  • Rotshteyn, A. P (1999). Intellektual'nyye tekhnologii identifikatsii: nechotkiye mnozhestva, geneticheskiye algoritmy, neyronnyye seti. Vinnitsa: "UNIVERSUM", 320.
  • Mazhara, O. A. (2015). Treat algorithm implementation by the basic matchalgorithm based on CLIPS programming environmen. Elektronnoye modelirovaniye, 37 (5), 61‒75.
  • Bolotova, S. Yu., Makhortov, S. D. (2011). Algoritmy relevantnogo obratnogo vyvoda na osnove resheniya produktsionno-logicheskikh uravneniy. Iskusstvennyy intellekt prinyatiye resheniyi, 2, 40‒50.
  • Zhyvotovskyi, R. M., Shyshatskyi, A. V., Petruk, S. N. (2017). Structural-semantic model of communication channel. Problems of Infocommunications. Science and Technology. Kharkiv, 524–529. doi: https://doi.org/10.1109/infocommst.2017.8246454