AI-Integrated Cloud Security and Privacy Framework for Protecting Healthcare Network Information and Cross-Team Collaborative Processes
DOI:
https://doi.org/10.15662/IJEETR.2023.0502006Keywords:
Cloud security, AI integration, healthcare networks, privacy preservation, cross-team collaboration, threat detection, adaptive access control, compliance managementAbstract
The rapid evolution of digital healthcare ecosystems and the surge in multi-team collaboration activities have intensified the need for next-generation security and privacy technologies capable of protecting sensitive clinical and operational data. This study introduces an innovative AI-integrated cloud security and privacy architecture engineered to deliver end-to-end protection for healthcare network environments while enabling seamless, trustworthy collaboration among distributed teams. The architecture harnesses cutting-edge machine learning intelligence—combining behavioral threat modeling, context-aware anomaly detection, and predictive cyber-risk analytics—to identify and neutralize security breaches before they escalate. Dynamic and self-adjusting access control mechanisms continuously evaluate user intent and environmental context, while autonomous encryption pipelines ensure uninterrupted, highly secure data movement across multi-layer cloud and network infrastructures.
To strengthen data confidentiality, the framework incorporates advanced privacy-preserving AI strategies such as federated learning for decentralized model training without exposure of sensitive records, and differential privacy to deliver rigorous, mathematically backed privacy guarantees. Integrated governance modules provide real-time compliance validation, automated policy orchestration, and end-to-end secured communication channels aligned with global healthcare regulations. Experimental findings demonstrate that the proposed framework significantly enhances resilience against complex cyber threats, minimizes unauthorized access risks, and maintains operational continuity in high-intensity, multi-team healthcare environments. Ultimately, this innovative architecture establishes a future-ready, scalable, and regulation-aligned foundation for intelligent healthcare security and secure collaborative data management in next-generation digital health systems.
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