Artificial Intelligence for Cloud Security and Threat Detection: A Review Study
Abstract
Cloud computing environments face increasing cybersecurity threats due to the rapid growth of distributed systems, multi-tenant architectures, and large-scale data sharing. This review paper investigates the role of Artificial Intelligence techniques in enhancing cloud security, cyber threat detection, and intelligent risk management. The study examines machine learning, anomaly detection, behavioral analytics, deep learning, and AI-driven intrusion detection systems used to secure cloud infrastructures and services. Existing literature is systematically reviewed to analyze attack detection accuracy, automated incident response mechanisms, and adaptive cybersecurity frameworks in cloud ecosystems. The paper further highlights challenges associated with adversarial AI attacks, data privacy regulations, explainability, and real-time threat intelligence processing. The review concludes that AI-based cloud security solutions provide substantial improvements in proactive threat mitigation and intelligent cyber defense strategies.
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