Security Model for the privacy of Big Data in Health Care Cloud using Fog Computing - Al-Khafaji, Rasha Basim Yousif (Universitas Muhammadiyah Sidoarjo, 2025)
General Background: The rapid integration of big data within health care cloud systems has transformed clinical data management but also intensified concerns regarding security and patient privacy. Specific Background: Existing cloud-based health infrastructures struggle to ensure confidentiality, integrity, and low-latency access, particularly as data volumes grow and computational demands increase. Knowledge Gap: Current models emphasize encryption or access control in isolation and provide limited solutions for latency, localized processing, and multi-layer threat detection, with minimal exploration of fog computing as an integrated security enhancer. Aims: This study proposes a comprehensive security framework that strengthens privacy protection for big data in health care cloud environments through combined encryption, role-based access control, anomaly detection, and fog computing integration. Results: Simulation-based evaluation demonstrates notable improvements, including reduced latency, enhanced data privacy, and high fog-node efficiency, indicating effective real-time processing and minimized exposure of sensitive data. Novelty: The model introduces a multilayered security architecture that strategically incorporates fog nodes to enable localized analysis, secure key management, and dynamic threat detection, offering a holistic approach absent from prior studies. Implications: The findings highlight a scalable and efficient security paradigm capable of improving resilience, privacy preservation, and operational performance in modern cloud-based health care systems.Highlight : The model integrates encryption, RBAC, and anomaly detection to strengthen data confidentiality in cloud-based healthcare systems. Fog computing reduces latency and limits data exposure by enabling localized processing near data sources. Simulation results show notable gains in latency reduction, data privacy, and fog node efficiency. Keywords : Health Care Cloud Security, Big Data Privacy, Fog Computing, Encryption in Healthcare, Anomaly Detection in Cloud Systems.