Navigating the Nexus of Cloud Security, Artificial Intelligence, And Regulatory Governance: A Multidisciplinary Framework for Scalable and Secure Data Ecosystems
Keywords:
Cloud Computing Security, Artificial Intelligence, Regulatory Compliance, E-HealthAbstract
The rapid migration of sensitive industrial and personal data to cloud-based infrastructures has necessitated a paradigm shift in how security, privacy, and compliance are managed. This research article provides an extensive investigation into the multifaceted challenges of cloud computing security, specifically within the e-health and financial sectors. By synthesizing contemporary literature on isolation infrastructures, attribute-based signcryption, and AI-driven regulatory compliance, this study establishes a comprehensive framework for "Sustainable Cloud Computing." The research explores the technical intricacies of securing Big Data and Internet of Things (IoT) environments, emphasizing the role of Resilient Distributed Datasets (RDDs) and automated metadata management. A significant portion of the analysis is dedicated to the emergence of "Compliance-as-Code," exemplified by HIPAA-automated audit trails in machine learning pipelines, and the integration of cognitive computing into next-generation intelligent information systems. Furthermore, the article addresses the geographic nuances of cloud security, the risks of cloud sourcing in public health, and the application of textual analysis in regulatory impact assessment. The findings suggest that a hybrid approach, combining advanced cryptographic protocols with AI-mediated operational optimization, is essential for mitigating the risks of model bias and data leakage. This study concludes by proposing a roadmap for future research in ontology-based provenance and fault-tolerant in-memory cluster computing.
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Copyright (c) 2026 Emily Carter Bennit
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