ArticleScientific reports2026
Blockchain-enabled data management system of internet of medical things.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 authors.
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Abstract
The Internet of Medical Things (IoMT) faces critical security challenges, including vulnerability to cyber-attacks, data forgery, and unauthorized access, due to its historically centralized architecture and insufficient built-in device security. This paper presents an integrated consortium blockchain-enabled data management system for IoMT environments, focusing on secure and auditable management of data generated by heterogeneous medical instruments. The system implements a multi-layered architecture comprising data, network, consensus, contract, and application layers. It employs RAFT for ledger commitment among authorized consortium nodes, SHA256 hashing and RSA digital signatures for transaction integrity verification and source authentication, and an RBAC-centered hybrid authorization model with metadata-index-assisted retrieval. Under a standardized workload of 10,000 health-data transactions across 4-10 consortium nodes, the proposed system achieved a throughput of 260-480 transactions per second and an average index-assisted query latency of 45-65 ms. Throughput decreased as the number of nodes increased, whereas query latency remained below 65 ms across all evaluated configurations. The proposed consortium blockchain framework supports integrity-protected, access-controlled, and auditable IoMT data management. Within the evaluated simulation setting, the system achieved sub-65 ms index-assisted query latency. Further deployment-oriented validation is required to characterize consensus and propagation latency, computational and storage overhead, energy consumption, and crash-fault recovery performance.
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