A Cloud-based IoMT Data Sharing Scheme with Conditional Anonymous Source Authentication

Yan Ping WANG, Xiao Fen WANG*, Hong Ning DAI, Xiao Song ZHANG, Yu SU, Muhammad IMRAN, Nidal NASSER

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

2 Citations (Scopus)

Abstract

As a rapidly growing subset of the Internet of Thing (IoT), the cloud-based Internet of Medical Thing (IoMT) has been widely applied in remote healthcare industries, which allows the physicians to monitor patients' body parameters remotely to offer continuous and timely healthcare. These healthcare parameters usually contain sensitive information, such as heart rates, glucose levels and etc., and the exposure of them may pose serious threats to the patients' health and lives. To guarantee security and privacy, many IoMT data sharing schemes have been proposed. However, most of these schemes either exhibit a one-to-one data sharing structure or fail to protect the patients' privacy. Since the data usually needs to be shared to different physicians, patients may want to be assisted without revealing their identities. To meet these requirements in healthcare systems, we propose a multi-receiver secure healthcare data sharing scheme, in which the patients are allowed to share their IoMT data to multiple physicians simultaneously for a multidisciplinary treatment, and the conditional anonymity is achieved where data source authentication is provided without revealing the patient's identity. When the patient health condition is abnormal, the hospital can correctly and quickly trace the patient's identity and inform him/her immediately. Our scheme is formally proved to achieve multiple security properties including confidentiality, unforgeability and anonymity. Simulation results demonstrate that the proposed scheme is efficient and practical.

Original languageEnglish
Title of host publication2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2915-2920
Number of pages6
ISBN (Electronic)9781665435406
ISBN (Print)9781665435406
DOIs
Publication statusE-pub ahead of print - 11 Jan 2023
Event2022 IEEE Global Communications Conference, GLOBECOM 2022 - Virtual, Online, Brazil
Duration: 4 Dec 20228 Dec 2022

Publication series

Name2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings

Conference

Conference2022 IEEE Global Communications Conference, GLOBECOM 2022
Country/TerritoryBrazil
CityVirtual, Online
Period4/12/228/12/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Funding

This work was partly supported by Natural Science Foundation (U19A2066) and the National Key RD Program of China (2021YFB3101300, 2021YFB3101302).

Keywords

  • anonymous authentication
  • Cloud-based IoMT
  • data sharing
  • healthcare
  • privacy-preserving

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