Regulatory Challenges and Frameworks for Fog Computing in Healthcare

Jeyaraman, Naveen and Ramasubramanian, Swaminathan and Yadav, Sankalp and Balaji, Sangeetha and Muthu, Sathish and Jeyaraman, Madhan (2024) Regulatory Challenges and Frameworks for Fog Computing in Healthcare. Cureus. pp. 1-12.

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Abstract

The integration of fog computing into healthcare promises significant advancements in real-time data analytics and patient care by decentralizing data processing closer to the source. This shift, however, introduces complex regulatory, privacy, and security challenges that are not adequately addressed by existing frameworks designed for centralized systems. The distributed nature of fog computing complicates the uniform application of security measures and compliance with diverse international re gulations, raising concerns about data privacy, security vulnerabilities, and legal accountability. This review explores these challenges in depth, discussing the implications of fog computing's decentralized architecture for data privacy, the difficulties in achieving consistent security across dispersed nodes, and the complexities of ensuring compliance in multi-jurisdictional environments. It also examines specific regulatory frameworks, including Health Insurance Portability and Accountability (HIPAA) in the United States, General Data Protection Regulation (GDPR) in the European Union, and emerging laws in Asia and Brazil, highlighting the gaps and the need for regulatory evolution to better accommodate the nuances of fog computing. The review advocates for a proactive regulatory approach, emphasizing the development of specific guidelines, international collaboration, and public-private partnerships to enhance compliance and support innovation. By embedding privacy and security by design and leveraging advanced technologies, healthcare providers can navigate the regulatory landscape effectively, ensuring that fog computing realizes its full potential as a transformative healthcare technology without compromising patient trust or data integrity.

Item Type: Article
Subjects: Social Media
Research Methods
Artificial Intelligence
Divisions: Biotechnology
Information Technology
Depositing User: Mr Repository Admin
Date Deposited: 01 Jan 2026 08:58
Last Modified: 01 Jan 2026 08:58
URI: https://ir.orthopaedicresearchgroup.com/id/eprint/368

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