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RISK ANALYSIS AND MITIGATION STRATEGIES FOR NATIONAL CRITICAL INFORMATION INFRASTRUCTURE AMIDST GROWING SECURITY THREATS

https://doi.org/10.26583/vestnik.2025.1.7

EDN: UPLTPD

Abstract

The rapid increase in cyberattacks targeting critical components of Russia’s information infrastructure — from banking systems and energy complexes to telecommunications networks — underscores the need for comprehensive and adaptive cybersecurity measures. This study aims to develop approaches that enable not only the efficient allocation of cybersecurity resources but also the prioritization of threats based on their criticality, which is especially important for protecting the system’s most vulnerable links. A detailed analysis of infrastructure vulnerabilities has been conducted, identifying key risk areas that require prioritized protection. Particular attention is given to the necessity of coordination between public and private sectors, as well as the integration of artificial intelligence technologies. Such technologies enhance both the accuracy of cyberattack forecasting and the efficiency of response actions. The study's findings emphasize the importance of implementing adaptive standards and multi-level collaboration for the effective protection of critical assets. This flexible, coordinated approach to cybersecurity strengthens the resilience of national infrastructure in the face of escalating cyber threats. Additionally, the integration of comprehensive technologies alongside standardized methods creates the potential for a flexible defense system capable of swiftly adapting to emerging threats and enabling continuous monitoring of critical assets.

About the Author

I. A. Vasilenko
Sirius University
Russian Federation


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For citations:


Vasilenko I.A. RISK ANALYSIS AND MITIGATION STRATEGIES FOR NATIONAL CRITICAL INFORMATION INFRASTRUCTURE AMIDST GROWING SECURITY THREATS. Vestnik natsional'nogo issledovatel'skogo yadernogo universiteta "MIFI". 2025;14(1):79-84. (In Russ.) https://doi.org/10.26583/vestnik.2025.1.7. EDN: UPLTPD

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