Interlinked Vulnerabilities in Cloud Ecosystems: A Correlation-Centric Taxonomy of Multidimensional Security Dynamics

Cloud security is an expanding domain, propelled by the growing incorporation of cloud computing into essential infrastructures and future technologies such as IoT and 5G. Although there is increasing study on cloud vulnerabilities, current studies frequently examine these issues in isolation, overlooking the complex interdependencies that impair hazards throughout the ecosystem. This research introduces a new, correlation-focused taxonomy that elucidates the interconnected vulnerabilities in cloud systems. This paper offers a multidimensional paradigm for comprehending and tackling cloud security concerns by analysing security dynamics from five critical perspectives: service models, architecture, networking, stakeholders and data. The research conducts a thorough systematic literature review (SLR) to identify essential characteristics and metrics that underlie cloud vulnerabilities. Moreover, the paper applies Statistical validation methods like frequency analysis, factor analysis and the Kaiser-Meyer–Olkin (KMO) test on the identified challenges, highlighting the interdependencies across the five perspectives and emphasizing where targeted interventions can yield the greatest impact along with the necessary cohesive solutions. The review connects theoretical insights with useful implementation instructions by defining eight critical metrics for service-model security and deriving four key variables from the five perspectives. This approach underscores the need for standardised frameworks, robust encryption, proactive monitoring and adaptive policies that respond to evolving threats. This research provides a comprehensive framework for addressing the intricate issues of cloud security by integrating taxonomic and statistical viewpoints. The results highlight the necessity for integrated, interdisciplinary approaches to protect cloud ecosystems amid growing interconnection.