Skip to content
Open access

Converging Infrastructure and Security: A Maturity-Based Approach to Cloud-Native Data Protection, SIEM Optimization, and Compliance Automation

2024 · International Journal of Artificial Intelligence, Data Science and Machine Learning · 0 citations

Abstract

Modern enterprises increasingly struggle to manage cloud security architecture, infrastructure resilience, SIEM operations, and regulatory compliance as isolated disciplines, resulting in operational inefficiencies, increased cyber risk, and costly audit processes. This paper presents a comprehensive five-level maturity model that unifies these traditionally disconnected domains into a cohesive framework for enterprise cybersecurity transformation. The proposed maturity model comprising Fragmented, Instrumented, Correlated, Automated, and Adaptive stages provides organizations with a practical roadmap for assessing current capabilities and systematically advancing toward intelligent, self-optimizing security operations. Unlike conventional reference architectures that assume green field deployments, the framework addresses the realities of heterogeneous enterprise environments spanning multi-cloud platforms, storage infrastructures, backup systems, security information and event management (SIEM) solutions, and compliance programs. The study further introduces diagnostic decision flows, capability maps, maturity transition guidance, and comparative operational metrics demonstrating improvements in incident detection, containment, backup resilience, compliance coverage, and automation maturity. By emphasizing the convergence of cloud infrastructure, cybersecurity operations, data protection, and governance through automation and cross-functional collaboration, the proposed framework enables organizations to reduce operational complexity, strengthen cyber resilience, accelerate regulatory compliance, and establish adaptive security capabilities suitable for modern cloud-native enterprises.

Read PDF