AI-Based System for Preventing and Automated Response to Cybersecurity Attacks

Abstract

This article discusses the role of artificial intelligence technologies in detecting cybersecurity threats in advance, monitoring them in real time, and developing automated response mechanisms. The study evaluates the effectiveness of AI-based threat prediction models, particularly Machine Learning and Deep Learning algorithms, and analyzes the process of integrating them into traditional security systems. In addition, the advantages of automated incident-response modules that enable instant, human-free reaction to cyberattacks, as well as their risk levels and impact on overall system stability, are examined. The findings show that AI-powered systems can significantly enhance accuracy, speed, and overall security in cybersecurity management.