MASS: A Multiattribute Sketch Secure Data Sharing Scheme for IoT Wearable Medical Devices Based on Blockchain

With the swift advancement of the Internet of Things (IoT) and artificial intelligence (AI), various technologies have been integrated into wearable medical health devices, improving users’ awareness of their physical states and enabling the analysis of a greater amount of human data. However, these sensitive pieces of information are prone to tampering or theft during storage and transmission, posing security risks. In this article, we propose a multiattribute sketch secure data sharing scheme for IoT wearable medical devices based on blockchain (MASS). We introduce a multiattribute sketch storage method that stores the encrypted hash of health data transmitted by medical wearable devices on the blockchain. This work also designs a ciphertext-policy attribute-based encryption (CP-ABE) access control mechanism that effectively addresses the secure sharing of data from wearable medical devices among healthcare professionals. Experimental findings indicate that with the rise in the number of medical health data documents, the costs associated with index generation and search time decrease by 55.3% and 10.83%, respectively. Additionally, as the frequency of data access increases, there is a 13.5% reduction in encryption time, and the implementation of multiattribute sketches results in a 24.8% and 11.3% reduction in index generation and search times, respectively.

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Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-09-26
DOI
https://doi.org/10.1109/jiot.2024.3468733
Citations
10
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
7.79

Funders

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article

MASS: A Multiattribute Sketch Secure Data Sharing Scheme for IoT Wearable Medical Devices Based on Blockchain

Lin Chen, Kuanching Li, Yuxiang Chen, Wei Liang et al.
10 citations
IEEE Internet of Things Journal
Blockchain Technology Applications and Security
7.79
article

MASS: A Multiattribute Sketch Secure Data Sharing Scheme for IoT Wearable Medical Devices Based on Blockchain

Lin Chen, Kuanching Li, Yuxiang Chen, Wei Liang, Xiong Li, Naixue Xiong, Jin Wang
article en
10 citations

Abstract

With the swift advancement of the Internet of Things (IoT) and artificial intelligence (AI), various technologies have been integrated into wearable medical health devices, improving users’ awareness of their physical states and enabling the analysis of a greater amount of human data. However, these sensitive pieces of information are prone to tampering or theft during storage and transmission, posing security risks. In this article, we propose a multiattribute sketch secure data sharing scheme for IoT wearable medical devices based on blockchain (MASS). We introduce a multiattribute sketch storage method that stores the encrypted hash of health data transmitted by medical wearable devices on the blockchain. This work also designs a ciphertext-policy attribute-based encryption (CP-ABE) access control mechanism that effectively addresses the secure sharing of data from wearable medical devices among healthcare professionals. Experimental findings indicate that with the rise in the number of medical health data documents, the costs associated with index generation and search time decrease by 55.3% and 10.83%, respectively. Additionally, as the frequency of data access increases, there is a 13.5% reduction in encryption time, and the implementation of multiattribute sketches results in a 24.8% and 11.3% reduction in index generation and search times, respectively.

IEEE Internet of Things JournalVol. 12(2)
Hunan University of Science and Technology (CN), University of Electronic Science and Technology of China (CN), Providence University (TW)
National Natural Science Foundation of China, Natural Science Foundation of Hunan Province, Science and Technology Program of Hunan Province, National Key Research and Development Program of China
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
7.79
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