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一种集成区块链和边缘计算的安全医疗数据框架:基于属性的签密方法。

A Secure Medical Data Framework Integrating Blockchain and Edge Computing: An Attribute-Based Signcryption Approach.

作者信息

Dou Tengyue, Zheng Zhiming, Qiu Wangjie, Ge Chunxia

机构信息

The Second School of Clinical Medicine, Binzhou Medical University, Yantai 264003, China.

Health Blockchain Research Center, Binzhou Medical University, Yantai 264003, China.

出版信息

Sensors (Basel). 2025 Apr 30;25(9):2859. doi: 10.3390/s25092859.

Abstract

With the rapid digitization of healthcare information, ensuring the security and privacy of patient data has become a critical research focus. This study introduces a novel Attribute-Based Signcryption (ABSC) framework combining blockchain and edge computing technologies to efficiently and securely manage medical data. The framework collects data via smart devices, which is then processed and encrypted at edge nodes and stored securely on the blockchain. Access to sensitive information is controlled with precision by predefined attribute sets, ensuring that only authorized users can retrieve the data. The experimental results demonstrate the significant advantages of this framework in improving data security, reducing computational overhead, and enhancing access efficiency.

摘要

随着医疗保健信息的快速数字化,确保患者数据的安全性和隐私性已成为关键的研究重点。本研究引入了一种结合区块链和边缘计算技术的新型基于属性的签密(ABSC)框架,以高效、安全地管理医疗数据。该框架通过智能设备收集数据,然后在边缘节点进行处理和加密,并安全地存储在区块链上。通过预定义的属性集精确控制对敏感信息的访问,确保只有授权用户才能检索数据。实验结果证明了该框架在提高数据安全性、降低计算开销和提高访问效率方面的显著优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb90/12074239/f04d2e820d37/sensors-25-02859-g001.jpg

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