In today’s world, information technology is rapidly evolving, leading to an increase in both the number and complexity of cyber threats, including phishing, malware, and social engineering attacks. The growth in the quantity and sophistication of cyber threats creates an urgent need to improve methods for protecting information systems. Artificial Intelligence (AI), particularly machine learning and deep learning technologies, shows significant potential in enhancing cybersecurity. This article is dedicated to reviewing contemporary AI-based cybersecurity methods and strategies, as well as evaluating their effectiveness in detecting and countering cyber threats. The paper analyzes recent research by both domestic and international scientists, emphasizing AI’s ability to analyze large volumes of data, uncover hidden patterns, predict potential threats, and automate incident response processes. It highlights key research directions, including anomaly detection, threat modeling, incident response automation, and ensuring the interpretability of decisions made by AI systems. Special attention is given to the integration of AI into existing cybersecurity systems and its capacity to adap
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