Blockchain-Enabled Trustworthy Healthcare Data Sharing Mechanism for Reliable 6G-IoT Networks
Qiang Zhang, Xingsi Xue, Jing Yang · IEEE Internet of Things Journal · 2025
With the implementation of 6G networks and IoT devices within the healthcare sector, the collection, processing, and utilization of medical data has changed significantly and, at the same time, generated massive amounts of patient information in disparate spaces. Such technological integrations allow for real-time monitoring, AI-assisted diagnostics, and individualized treatment protocols that were not possible before. However, centralized healthcare data management systems encounter substantial obstacles, including single points of failure, limited patient control over personal information, vulnerability to cyber-attacks, and complex regulatory compliance issues. This paper proposes BTHRiD, a blockchain-enabled, trustworthy healthcare, reliable IoT data-sharing mechanism for 6G networks. BTHRiD introduces a proof-of-storage consensus mechanism combining block validation with decentralized medical data storage and a layered propagation approach for efficient data distribution across healthcare nodes. Through mathematical modeling, we analyze block propagation latency and network decentralization characteristics, deriving optimal operational points for healthcare data sharing. Experimental results show that the proposed BTHRiD outperforms other solutions by 34% in processing latency and 28% in detection accuracy of malicious behavior. BTHRiD’s practical effectiveness is demonstrated in a real-world implementation example of tracking COVID-19 patient trajectories where data consistency was preserved at 96% during recovery phases while achieving a 42% reduction in storage overhead. Additional telemedicine, EHR sharing, and clinical trial application testing confirm the system’s adaptability to diverse healthcare requirements. The proposed mechanism enables secure, efficient, and trustworthy medical data sharing in 6G-IoT healthcare networks while preserving patient privacy and ensuring data reliability across heterogeneous healthcare environments.