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ARTIFICIAL INTELLIGENCE IN CYBER THREATS: OPPORTUNITIES AND CHALLENGES OF USING NEURAL NETWORKS FOR PHISHING ATTACKS AND THEIR DETECTION

Donskikh Nikita Igorevich  (Postgraduate student of the Department of Information Security, Financial University under the Government of the Russian Federation Moscow, Russia )

This article examines the impact of artificial intelligence, in particular large language models, on the evolution of phishing attacks, as well as the possibilities of countering these threats using classification neural networks. It considers the methods that attackers use to create personalized and convincing phishing messages, and analyzes the effectiveness of neural networks in their detection and prevention. Particular attention is paid to the importance of balancing the development of AI technologies and their regulation to ensure cybersecurity. In conclusion, technical, legal and ethical measures aimed at regulating and safely using these technologies are proposed.

Keywords:artificial intelligence, large language models, phishing attacks, neural networks, classification models, cybersecurity, AI regulation, social engineering, personalization of attacks, AI technologies
 

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Citation link:
Donskikh N. I. ARTIFICIAL INTELLIGENCE IN CYBER THREATS: OPPORTUNITIES AND CHALLENGES OF USING NEURAL NETWORKS FOR PHISHING ATTACKS AND THEIR DETECTION // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№01. -С. 70-73 DOI 10.37882/2223-2966.2025.01.16
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