AI-Driven Threat Detection In Multi-Cloud Environments

The rapid adoption of multi-cloud environments has fundamentally transformed enterprise IT infrastructure, offering enhanced scalability, resilience, and vendor flexibility. However, this architectural evolution has also introduced complex security challenges, including fragmented visibility, heterogeneous security policies, and increased attack surfaces. Traditional security mechanisms, which rely heavily on static rules and signature-based detection, are often inadequate in addressing the dynamic and distributed nature of multi-cloud ecosystems. In this context, artificial intelligence has emerged as a transformative approach to modern cybersecurity, enabling adaptive, real-time threat detection and response. This review article explores the role of artificial intelligence in enhancing threat detection capabilities across multi-cloud environments. It systematically examines the integration of machine learning, deep learning, and behavioral analytics into cloud security frameworks, emphasizing their ability to identify anomalous activities, predict potential threats, and automate incident response. The study also evaluates key architectural components, including data ingestion pipelines, model training strategies, and cross-cloud orchestration mechanisms that support AI-driven security systems. Furthermore, the article discusses the challenges associated with implementing AI in multi-cloud security, such as data privacy concerns, model interpretability, adversarial attacks, and scalability constraints. It highlights emerging trends, including federated learning, zero-trust architectures, and autonomous security operations, which are shaping the future of intelligent threat detection systems. Comparative insights into existing frameworks and industry practices are also provided to illustrate the practical implications of AI adoption. By synthesizing current research and technological advancements, this review aims to provide a comprehensive understanding of AI-driven threat detection in multi-cloud environments. It offers a strategic roadmap for researchers and practitioners to design robust, scalable, and intelligent security solutions capable of addressing evolving cyber threats in increasingly complex cloud infrastructures.