A federated trust enforcement architecture for secure cross-organizational EHR access over 5G-enabled medical IoT networks
The advent of the Internet of Things (IoT) technologies in healthcare has significantly changed the ways in which patient health information is collected, communicated, and managed within a wide array of geographically distributed healthcare ecosystem. The technological convergence not only increases clinical responsiveness but also creates significant issues related to trusted, interoperable cross-domain sharing of electronic health records (EHRs). Existing federated learning systems do not have tools to handle bad actors, implement zero-trust policies for access across organizational boundaries, or offer formally provable security guarantees. To address these challenges, this research work introduces Fed-ZTMA, a Federated Zero-Trust Medical Access Framework that combines the Byzantine-resilient weighted federated trust aggregation with adaptive zero-trust policy enforcement via Blockchain deployed smart contracts. The proposed framework splits the Synthea Synthetic EHR dataset across four independent logical healthcare organizations and assesses performance using a multi-node Ganache Ethereum testnet with seven different adversarial attack scenarios. Compared to existing approach such as FedHealthDP, BCMedShare, ZeroTrust-IoT, BlockEHR, and ABAC-Chain, Proposed Fed-ZTMA performs better, including a cross-organization access success rate of 98.7%, attack suppression rate of 97.9%, inter-domain access latency of 18.4 ms at 1000 devices, and security stability index of 96.4%. This research work demonstrates practical feasibility for multi-institutional 5G healthcare deployments where both privacy-preservation and Byzantine fault tolerance are mandatory requirements.
Authors
- S. Ramya
- S. Karthik
- V. Praveena
Institutions
- Coimbatore Medical College and Hospital (IN)
- PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Publication Details
- Journal
- Scientific Reports
- Published
- 2026-08-20
- DOI
- https://doi.org/10.1038/s41598-026-66517-x
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00