A Privacy-Protection Model for Patients
Joint Authors
Yin, Xiangdong
Liu, Chunyan
Cheng, Wenzhi
Ou, Wei
Yan, Wanqin
Liu, Dingwan
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
The collection and analysis of patient cases can effectively help researchers to extract case feature and to achieve the objectives of precision medicine, but it may cause privacy issues for patients.
Although encryption is a good way to protect privacy, it is not conducive to the sharing and analysis of medical cases.
In order to address this problem, this paper proposes a federated learning verification model, which combines blockchain technology, homomorphic encryption, and federated learning technology to effectively solve privacy issues.
Moreover, we present a FL-EM-GMM Algorithm (Federated Learning Expectation Maximization Gaussian Mixture Model Algorithm), which can make model training without data exchange for protecting patient’s privacy.
Finally, we conducted experiments on the federated task of datasets from two organizations in our model system, where the data has the same sample ID with different subset features, and this system is capable of handling privacy and security issues.
The results show that the model was trained by our system with better usability, security, and higher efficiency, which is compared with the model trained by traditional machine learning methods.
American Psychological Association (APA)
Cheng, Wenzhi& Ou, Wei& Yin, Xiangdong& Yan, Wanqin& Liu, Dingwan& Liu, Chunyan. 2020. A Privacy-Protection Model for Patients. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1208491
Modern Language Association (MLA)
Cheng, Wenzhi…[et al.]. A Privacy-Protection Model for Patients. Security and Communication Networks No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1208491
American Medical Association (AMA)
Cheng, Wenzhi& Ou, Wei& Yin, Xiangdong& Yan, Wanqin& Liu, Dingwan& Liu, Chunyan. A Privacy-Protection Model for Patients. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1208491
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208491