Cybersecurity in Data Centers Based on Artificial Intelligence

Abstract

This article examines the problems and solutions related to cybersecurity in data centers based on artificial intelligence. With the growing role of digital technologies and the increase in the volume of processed data, data centers are becoming critical infrastructure requiring a high level of protection. The integration of artificial intelligence into the cybersecurity management of these systems enables automated threat detection, real-time network traffic analysis, and adaptive incident response. The aim of the article is to present a systematic analysis of the main cyber threats affecting modern data centers, to evaluate existing protection methods, and to explore the role of artificial intelligence as a tool for increasing their security and autonomy. Additionally, it aims to identify problems related to the implementation of intelligent systems, as well as outline trends in the development of secure and self-governing infrastructures. The results achieved include a classification of the main types of cyber threats, an assessment of the effectiveness of traditional defense mechanisms, and an analysis of the advantages of AI-based approaches, including machine learning algorithms, deep learning, and behavioral analysis. The study shows that the use of intelligent systems significantly improves the ability to detect anomalies early, reduces incident response time, and increases the resilience of the infrastructure against complex and unknown attacks.