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Prospects for the Introduction of Artificial Intelligence to Detect and Block Cyber Threats in the Financial Sphere of the Ministry of Internal Affairs

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dc.contributor.author Synytsina, Yuliia
dc.date.accessioned 2026-05-21T05:59:20Z
dc.date.available 2026-05-21T05:59:20Z
dc.date.issued 2026
dc.identifier.issn 3100-5527
dc.identifier.uri https://irek.ase.md:443/xmlui/handle/123456789/4863
dc.description SYNYTSINA, Yuliia. Prospects for the Introduction of Artificial Intelligence to Detect and Block Cyber Threats in the Financial Sphere of the Ministry of Internal Affairs. Online. In: Proceedings of the 29th International Scientific Conference Competitiveness and Innovation in the Knowledge Economy, Chișinău, Moldova, September 26-27, 2025. București: Editura ASE, 2026, pp. 567-570. ISSN 3100-5527. Disponibil: https://doi.org/10.24818/cike2025.70 en_US
dc.description.abstract The modern financial and economic processes within the Ministry of Internal Affairs of Ukraine face increasing complexity and exposure to sophisticated cyber threats. Traditional protection methods, including antivirus programs, filtering systems, and firewalls, have become insufficient due to the dynamic and targeted nature of contemporary cyberattacks. In response, the implementation of artificial intelligence (AI) and machine learning (ML) technologies has emerged as a critical approach for detecting, predicting, and mitigating threats in the financial sector. AI-based systems, including neural networks, enable intelligent decision support by analyzing user behavior, detecting anomalies, and forecasting risks in real time, thereby reducing the incidence of fraud, money laundering, and unauthorized access. Research has demonstrated that modeling antagonistic agent behavior and integrating adaptive AI systems can significantly decrease hybrid threat implementation, financial losses, and incident response time. The application of AI in public-sector financial operations involves automated monitoring of payments, contracts, and public procurement, as well as verification of counterparties and anomaly detection in transactions. Technical implementations employ flow analytics, graph models, behavioral profiling, and deepfake detection, supported by human-in-the-loop operational models. Compliance with regulatory and ethical standards, particularly the NIST AI Risk Management Framework, ensures transparency, reliability, and explainability of AI decisions. Challenges include high-quality data requirements, cost of implementation, offensive AI threats, and regulatory adherence. Pilot projects for AI/ML-based financial threat detection demonstrate the potential for rapid anomaly identification, improved fraud prevention, and enhanced overall financial security. Integrating intelligent systems thus strengthens the cyber resilience of the Ministry of Internal Affairs, supporting both operational efficiency and strategic risk management. JEL: G21, G28, G32, O33, C45 en_US
dc.language.iso en en_US
dc.publisher ASE en_US
dc.subject AI strengthens en_US
dc.subject MIA en_US
dc.subject financial cyber security en_US
dc.title Prospects for the Introduction of Artificial Intelligence to Detect and Block Cyber Threats in the Financial Sphere of the Ministry of Internal Affairs en_US
dc.type Article en_US


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