AI-Based Multi-Cloud Security Management Framework for Threat Detection, Risk Assessment, and Automated Incident Response.

Abstract

The rapid adoption of multi-cloud environments has transformed modern enterprise computing by enabling flexibility, scalability, and cost optimization. However, managing security across multiple cloud providers introduces challenges such as inconsistent security policies, fragmented visibility, identity management complexities, and evolving cyber threats. Traditional security solutions are often insufficient for providing unified protection across heterogeneous cloud infrastructures. This paper proposes an Artificial Intelligence (AI)-Based Multi-Cloud Security Framework that integrates machine learning, anomaly detection, threat intelligence, predictive risk assessment, and automated incident response. The framework continuously monitors cloud environments, identifies malicious activities, predicts security risks, and automates remediation actions. The proposed model enhances security posture, reduces incident response time, and improves compliance management. The framework demonstrates how AI can strengthen cybersecurity operations in modern multi-cloud architectures.

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