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: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (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
PublisherIEEE
Pages2915-2920
Number of pages6
ISBN (Electronic)9781665435406
ISBN (Print)9781665435413
DOIs
Publication statusPublished - Dec 2022
Event2022 IEEE Global Communications Conference, GLOBECOM 2022 - Virtual, Online, Rio de Janeiro, Brazil
Duration: 4 Dec 20228 Dec 2022
https://ieeexplore.ieee.org/xpl/conhome/10000063/proceeding

Publication series

NameIEEE Global Communications Conference (GLOBECOM) - Proceedings

Conference

Conference2022 IEEE Global Communications Conference, GLOBECOM 2022
Country/TerritoryBrazil
CityRio de Janeiro
Period4/12/228/12/22
Internet address

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality

User-Defined Keywords

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

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