APPLICATION OF GENERATIVE AI IN CYBERSECURITY DETECTION AND PREVENTION OF NEXT-GENERATION ATTACKS

Abstract

This article examines modern approaches to applying generative artificial intelligence (Generative AI) to cybersecurity problems. Particular attention is paid to the use of generative adversarial networks (GANs), large-scale language models (LLMs), and transformer architectures to detect, model, and prevent next-generation attacks, including zero - day attacks, polymorphic malware, and phishing.