AI-Driven Cybersecurity in Multi-Cloud Environments: Trends, Challenges, and Future Directions

Abstract

With the increasing adoption of multi-cloud infrastructures, cybersecurity threats have become more sophisticated and dynamic. Artificial Intelligence (AI) and Machine Learning (ML) are playing a pivotal role in enhancing threat detection, anomaly identification, and automated response systems. This review paper explores AI-driven cybersecurity frameworks tailored for multi-cloud environments. It examines deep learning-based intrusion detection systems, behavioral analytics, and zero-trust architectures. The paper also discusses challenges such as data fragmentation, model drift, and adversarial attacks. Emerging trends, including autonomous security operations and explainable AI in cybersecurity, are analyzed to provide insights into building resilient cloud ecosystems.