A Secure and Efficient Sharing Scheme for Medical IoT Data Based on Consortium Blockchain

Internet of things (IoT) is crucial for the hierarchical medical system, which enables the real-time monitoring and collection of data, thereby improving patient treatment outcomes. However, achieving secure, efficient, timely, and controllable medical IoT data sharing between higher-lever hospital (HLH) and lower-level hospital (LLH) is a challenging task for the hierarchical medical system. Consortium blockchain, which is an effective way to achieve secure and trustworthy data sharing, has the potential to address these issues. In this article, we propose a novel cloud-chain sharing scheme for medical IoT data based on consortium blockchain. In this scenario, HLH and LLH establish a consortium blockchain, where medical IoT data is stored both on-chain and off-chain. On-chain data adopt a proxy re-encryption based on elliptic curve cryptography (ECC-PRE) strategy and attribute-based strategy to facilitate secure access and controlled sharing of data. Off-chain data sharing provides three different modes, namely, private data collection (PDC), direct channel (DC), and cloud storage (CS), according to the urgency of patient and the sensitivity of the data. Furthermore, a file security breakpoint resume scheme, rooted in the consortium blockchain, and a file weighting strategy are employed to enhance the efficiency and timeliness of data sharing. Finally, the security and performance of our proposed scheme are verified, and the results demonstrate that our scheme is secure, feasible, and efficient.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-09-24
DOI
https://doi.org/10.1109/jiot.2025.3613722
Primary Topic
Big Data and Digital Economy
Type
article
Field-Weighted Citation Impact
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article

A Secure and Efficient Sharing Scheme for Medical IoT Data Based on Consortium Blockchain

Baozhan Chen, M. Shamim Hossain, Shahid Mumtaz, Athanasios V. Vasilakos et al.
IEEE Internet of Things Journal
Big Data and Digital Economy
article

A Secure and Efficient Sharing Scheme for Medical IoT Data Based on Consortium Blockchain

Baozhan Chen, M. Shamim Hossain, Shahid Mumtaz, Athanasios V. Vasilakos, Di Zhang, Yunkai Zhai, Xue Yang, Yan Qiao
article en

Abstract

Internet of things (IoT) is crucial for the hierarchical medical system, which enables the real-time monitoring and collection of data, thereby improving patient treatment outcomes. However, achieving secure, efficient, timely, and controllable medical IoT data sharing between higher-lever hospital (HLH) and lower-level hospital (LLH) is a challenging task for the hierarchical medical system. Consortium blockchain, which is an effective way to achieve secure and trustworthy data sharing, has the potential to address these issues. In this article, we propose a novel cloud-chain sharing scheme for medical IoT data based on consortium blockchain. In this scenario, HLH and LLH establish a consortium blockchain, where medical IoT data is stored both on-chain and off-chain. On-chain data adopt a proxy re-encryption based on elliptic curve cryptography (ECC-PRE) strategy and attribute-based strategy to facilitate secure access and controlled sharing of data. Off-chain data sharing provides three different modes, namely, private data collection (PDC), direct channel (DC), and cloud storage (CS), according to the urgency of patient and the sensitivity of the data. Furthermore, a file security breakpoint resume scheme, rooted in the consortium blockchain, and a file weighting strategy are employed to enhance the efficiency and timeliness of data sharing. Finally, the security and performance of our proposed scheme are verified, and the results demonstrate that our scheme is secure, feasible, and efficient.

IEEE Internet of Things JournalVol. 12(23)
Silesian University of Technology (PL), Sun Yat-sen University (CN), University of Agder (NO), King Saud University (SA), Zhengzhou University (CN), First Affiliated Hospital of Zhengzhou University (CN), Imam Abdulrahman Bin Faisal University (SA)
Openalex Percentile: Top 62%
Big Data and Digital Economy
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