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Privacy-preserving contact tracing in 5G-integrated and blockchain-based medical applications.
Zhang, Can; Xu, Chang; Sharif, Kashif; Zhu, Liehuang.
  • Zhang C; School of Computer Science & Technology, Beijing Institute of Technology, Beijing, China.
  • Xu C; School of Cyberspace Science & Technology, Beijing Institute of Technology, Beijing, China.
  • Sharif K; School of Computer Science & Technology, Beijing Institute of Technology, Beijing, China.
  • Zhu L; School of Cyberspace Science & Technology, Beijing Institute of Technology, Beijing, China.
Comput Stand Interfaces ; 77: 103520, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1071236
ABSTRACT
The current pandemic situation due to COVID-19 is seriously affecting our daily work and life. To block the propagation of infectious diseases, an effective contact tracing mechanism needs to be implemented. Unfortunately, existing schemes have severe privacy issues that jeopardize the identity-privacy and location-privacy for both users and patients. Although some privacy-preserving systems have been proposed, there remain several issues caused by centralization. To mitigate this issues, we propose a Privacy-preserving contact Tracing scheme in 5G-integrated and Blockchain-based Medical applications, named PTBM. In PTBM, the 5G-integrated network is leveraged as the underlying infrastructure where everyone can perform location checking with his mobile phones or even wearable devices connected to 5G network to find whether they have been in possible contact with a diagnosed patient without violating their privacy. A trusted medical center can effectively trace the patients and their corresponding close contacts. Thorough security and performance analysis show that the proposed PTBM scheme achieves privacy protection, traceability, reliability, and authentication, with high computation & communication efficiency and low latency.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Stand Interfaces Year: 2021 Document Type: Article Affiliation country: J.csi.2021.103520

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Stand Interfaces Year: 2021 Document Type: Article Affiliation country: J.csi.2021.103520