Generative Intelligence Framework for Secure Multi-Cloud Enterprise Operations and Cyber Resilience

Abstract

The rapid expansion of multi-cloud computing has transformed enterprise operations by enabling organizations to distribute applications, workloads, and data across multiple cloud providers. However, this transformation has also introduced significant challenges related to cybersecurity, operational complexity, data governance, compliance, threat detection, and business continuity. Conventional security approaches often struggle to understand dynamic relationships among cloud resources, user activities, applications, and emerging cyber threats. This paper proposes a Generative Intelligence Framework for Secure Multi-Cloud Enterprise Operations and Cyber Resilience. The proposed framework integrates generative artificial intelligence, machine learning, zero-trust security, automated threat analysis, policy intelligence, cloud-native security controls, and cyber-resilience mechanisms into a unified architecture. Generative intelligence is employed to synthesize security information, explain complex incidents, generate contextual risk assessments, recommend response strategies, and support security decision-making across heterogeneous cloud environments. The framework incorporates centralized governance with distributed enforcement to maintain consistent security policies across multiple cloud platforms. It also integrates continuous monitoring, identity-centric access control, encryption, anomaly detection, automated incident response, backup, disaster recovery, and adaptive learning. The research methodology uses a design-oriented approach involving architecture development, threat modeling, simulation, performance evaluation, and comparative analysis. The proposed framework can improve security visibility, operational efficiency, incident response, compliance, and organizational resilience while reducing the complexity of multi-cloud management.