A Privacy-Preserving Medical Data Sharing Scheme Based on Consortium Blockchain

Author(s):  
Jingwei Liu ◽  
Tianyu Liang ◽  
Rong Sun ◽  
Xiaojiang Du ◽  
Mohsen Guizani
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhuo Zhao ◽  
Chingfang Hsu ◽  
Lein Harn ◽  
Qing Yang ◽  
Lulu Ke

Internet of Medical Things (IoMT) is a kind of Internet of Things (IoT) that includes patients and medical sensors. Patients can share real-time medical data collected in IoMT with medical professionals. This enables medical professionals to provide patients with efficient medical services. Due to the high efficiency of cloud computing, patients prefer to share gathering medical information using cloud servers. However, sharing medical data on the cloud server will cause security issues, because these data involve the privacy of patients. Although recently many researchers have designed data sharing schemes in medical domain for security purpose, most of them cannot guarantee the anonymity of patients and provide access control for shared health data, and further, they are not lightweight enough for IoMT. Due to these security and efficiency issues, a novel lightweight privacy-preserving data sharing scheme is constructed in this paper for IoMT. This scheme can achieve the anonymity of patients and access control of shared medical data. At the same time, it satisfies all described security features. In addition, this scheme can achieve lightweight computations by using elliptic curve cryptography (ECC), XOR operations, and hash function. Furthermore, performance evaluation demonstrates that the proposed scheme takes less computation cost through comparison with similar solutions. Therefore, it is fairly an attractive solution for efficient and secure data sharing in IoMT.


2021 ◽  
Vol 58 (4) ◽  
pp. 102604
Author(s):  
Renpeng Zou ◽  
Xixiang Lv ◽  
Jingsong Zhao

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 28019-28027 ◽  
Author(s):  
Dong Zheng ◽  
Axin Wu ◽  
Yinghui Zhang ◽  
Qinglan Zhao

Author(s):  
Yu Niu ◽  
Ji-Jiang Yang ◽  
Qing Wang

With the pervasive using of Electronic Medical Records (EMR) and telemedicine technologies, more and more digital healthcare data are accumulated from multiple sources. As healthcare data is valuable for both commercial and scientific research, the demand of sharing healthcare data has been growing rapidly. Nevertheless, health care data normally contains a large amount of personal information, and sharing them directly would bring huge threaten to the patient privacy. This paper proposes a privacy preserving framework for medical data sharing with the view of practical application. The framework focuses on three key issues of privacy protection during the data sharing, which are privacy definition/detection, privacy policy management, and privacy preserving data publishing. A case study for Chinese Electronic Medical Record (ERM) publishing with privacy preserving is implemented based on the proposed framework. Specific Chinese free text EMR segmentation, Protected Health Information (PHI) extraction, and K-anonymity PHI anonymous algorithms are proposed in each component. The real-life data from hospitals are used to evaluate the performance of the proposed framework and system.


2019 ◽  
Vol 10 (6) ◽  
pp. 1-23 ◽  
Author(s):  
Wenjuan Tang ◽  
Ju Ren ◽  
Kuan Zhang ◽  
Deyu Zhang ◽  
Yaoxue Zhang ◽  
...  

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