ФОРМУВАННЯ ІНТЕЛЕКТУАЛЬНОЇ СИСТЕМИ ВИЯВЛЕННЯ ТА ПРОТИДІЇ АТАКАМ У СЕРЕДОВИЩІ 6G

Relevance. The rapid development of sixth-generation (6G) mobile networks and the integration of artificial intelligence, the Internet of Things (IoT), cyber-physical systems, and cloud and edge computing necessitate new approaches to detecting and countering cyber threats. The wide variety of modern threats creates a need for intelligent protection systems capable of continuous monitoring, threat classification, assessment of adversary capabilities, and the adaptive formulation of defensive actions. The subject of the study comprises methods and models for constructing an intelligent system to detect and counter cyber threats in a 6G environment, utilizing neural networks, a multi-loop protection architecture, integrated security assessment, and error-resilient coding. The purpose of the article is to develop an intelligent multi-loop protection system for critical information infrastructure assets within a 6G environment; this system integrates neural network-based threat classification, adversary capability assessment, matrix analysis of interrelationships between resources, threats, and infrastructure elements, and an integral assessment of the current level of cyber resilience. Results obtained. A structural model for an integrated threat classifier combining CNN and RNN/LSTM architectures is proposed; application areas for neural networks in cybersecurity are systematized; a conceptual model for an intelligent multi-loop protection system is formulated; an approach to assessing adversary capabilities based on computational, temporal, and financial resources is formalized; and the procedure for calculating an integrated security metric is defined. A comparative assessment of protection mechanisms was conducted based on a set of characteristics. Conclusion. The proposed approach ensures a comprehensive combination of intelligent threat detection, multi-layered protection, and quantitative assessment of the current security status. For the post-quantum component of the system, it is advisable to focus on standardized and promising code-based and lattice-based cryptographic mechanisms, supplemented by error-correcting coding. Such an architecture establishes a foundation for an adaptive system to counter cyber threats in 6G networks and critical infrastructure facilities.

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Journal
Scientific periodicals of Ukraine
Published
2026-09-20
Primary Topic
Cybersecurity and Information Systems
Type
article
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article

ФОРМУВАННЯ ІНТЕЛЕКТУАЛЬНОЇ СИСТЕМИ ВИЯВЛЕННЯ ТА ПРОТИДІЇ АТАКАМ У СЕРЕДОВИЩІ 6G

Тетяна Войтко, Ruslan Mamedov, Ельвін Юсубов, Лала Бякірова
Scientific periodicals of Ukraine
Cybersecurity and Information Systems
article

ФОРМУВАННЯ ІНТЕЛЕКТУАЛЬНОЇ СИСТЕМИ ВИЯВЛЕННЯ ТА ПРОТИДІЇ АТАКАМ У СЕРЕДОВИЩІ 6G

Тетяна Войтко, Ruslan Mamedov, Ельвін Юсубов, Лала Бякірова
article en

Abstract

Relevance. The rapid development of sixth-generation (6G) mobile networks and the integration of artificial intelligence, the Internet of Things (IoT), cyber-physical systems, and cloud and edge computing necessitate new approaches to detecting and countering cyber threats. The wide variety of modern threats creates a need for intelligent protection systems capable of continuous monitoring, threat classification, assessment of adversary capabilities, and the adaptive formulation of defensive actions. The subject of the study comprises methods and models for constructing an intelligent system to detect and counter cyber threats in a 6G environment, utilizing neural networks, a multi-loop protection architecture, integrated security assessment, and error-resilient coding. The purpose of the article is to develop an intelligent multi-loop protection system for critical information infrastructure assets within a 6G environment; this system integrates neural network-based threat classification, adversary capability assessment, matrix analysis of interrelationships between resources, threats, and infrastructure elements, and an integral assessment of the current level of cyber resilience. Results obtained. A structural model for an integrated threat classifier combining CNN and RNN/LSTM architectures is proposed; application areas for neural networks in cybersecurity are systematized; a conceptual model for an intelligent multi-loop protection system is formulated; an approach to assessing adversary capabilities based on computational, temporal, and financial resources is formalized; and the procedure for calculating an integrated security metric is defined. A comparative assessment of protection mechanisms was conducted based on a set of characteristics. Conclusion. The proposed approach ensures a comprehensive combination of intelligent threat detection, multi-layered protection, and quantitative assessment of the current security status. For the post-quantum component of the system, it is advisable to focus on standardized and promising code-based and lattice-based cryptographic mechanisms, supplemented by error-correcting coding. Such an architecture establishes a foundation for an adaptive system to counter cyber threats in 6G networks and critical infrastructure facilities.

Scientific periodicals of Ukraine
Azerbaijan State Oil and Industry University (AZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
Cybersecurity and Information Systems
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