Mathematical model and structure of a neural network for detection of cyber attacks on information and communication systems

• Autorzy: Zahoruiko, Lubov , Martianova, Tetiana , Al-Hiari, Mohammad , Polovenko, Lyudmyla , Kovalchuk, Maiia , Merinova, Svitlana , Shakhov, Volodymyr , Yeraliyeva, Bakhyt

Warianty tytułu

PL

Model matematyczny i struktura sieci neuronowej do wykrywania cyberataków na systemy teleinformatyczne i komunikacyjne

• Języki publikacji: EN

Abstrakty

EN

The paper discusses the principles of creating a mathematical model and system architecture by applying the method of artificial intelligence to detect cyberattacks on information and communication systems, where a neural network capable of learning and detecting cyberattacks is used. The proposed approach, based on the application of the developed mathematical model and architecture of artificial neural networks, as a detector of network attacks on information and communication systems, allows to increase the level of detection of network intrusions into computer systems, Web and Internet resources. An algorithm for processing network traffic parameters in real-time systems by structuring a neural network is proposed, which allows to optimize the redundancy of its multi-level structure at the level of inter-element connections.

PL

W artykule omówiono zasady tworzenia modelu matematycznego i architektury systemu poprzez zastosowanie metody sztucznej inteligencji do wykrywania cyberataków na systemy teleinformatyczne, gdzie wykorzystywana jest sieć neuronowa zdolna do uczenia się i wykrywania cyberataków. Proponowane podejście, oparte na zastosowaniu opracowanego modelu matematycznego i architektury sztucznych sieci neuronowych, jako detektora ataków sieciowych na systemy teleinformatyczne, pozwala na zwiększenie poziomu wykrywania włamań sieciowych do systemów komputerowych, zasobów sieciowych i internetowych. Zaproponowano algorytm przetwarzania parametrów ruchu sieciowego w systemach czasu rzeczywistego poprzez strukturyzację sieci neuronowej, co pozwala na optymalizację redundancji jej wielopoziomowej struktury na poziomie połączeń międzyelementowych.

Słowa kluczowe

PL

sieci neuronowe; ruch sieciowy; połączenie sieciowe; cyberatak; system teleinformatyczny

EN

neural networks; network traffic; network connection; cyber attack; information and communication system

• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2024
• Tom: T. 14, nr 3
• Strony: 49--55
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Zahoruiko, Lubov

• Vinnytsia National Technical University, Vinnytsia, Ukraine,
• Vasyl‘ Stus Donetsk National University, Vinnytsia, Ukraine

autor

Martianova, Tetiana

• Vinnytsia Regional Youth Centre Kvadrat, Vinnytsia, Ukraine,

autor

Al-Hiari, Mohammad

• Jadara University, Irbid, Jordan,

autor

Polovenko, Lyudmyla

• Vinnytsia National Technical University, Vinnytsia, Ukraine,

autor

Kovalchuk, Maiia

• Vinnytsia National Technical University, Vinnytsia, Ukraine,

autor

Merinova, Svitlana

• Vinnytsia Institute of Trade and Economics of State University of Trade and Economics, Vinnytsia, Ukraine,

autor

Shakhov, Volodymyr

• Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University, Vinnytsia, Ukraine,

autor

Yeraliyeva, Bakhyt

• M. Kh. Dulaty Taraz Regional University, Taraz, Kazakhstan,

Bibliografia

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• [18] Turlykozhayeva D. et al.: Routing Algorithm for Software Defined Network Based on Boxcovering Algorithm. 10th International Conference on Wireless Networks and Mobile Communications – WINCOM, 2023.
• [19] Turlykozhayeva D. et al.: Routing metric and protocol for wireless mesh network based on information entropy theory. Eurasian Physical Technical Journal 46, 2008, 90–98.
• [20] Ulichev O. S. et al.: Computer modeling of dissemination of informational influences in social networks with different strategies of information distributors. Proc. SPIE 11176, 2019, 111761T.
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Identyfikatory

DOI

10.35784/iapgos.6155