Multi-server assisted data sharing supporting secure deduplication for metaverse healthcare systems

Tao Zhang, Jian Shen, Chin Feng Lai, Sai Ji, Yongjun Ren

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


The integration of Metaverse and healthcare will improve the allocation and utilization of healthcare resources. Metaverse healthcare data is stored on a public server and downloaded using Artificial Intelligence devices. Patients are given a diagnosis promptly through Metaverse healthcare systems. However, storing Metaverse healthcare data on public servers leads to a variety of problems, such as leakage of patient health information and loss of vital medical record data. Attribute-based encryption (ABE) has played an important role in securely and efficiently Metaverse healthcare data sharing. In this paper, a feature-rich and efficient ABE-based Metaverse healthcare data sharing scheme is presented, which realizes constant encryption computation overhead according to a multi-server structure. To reduce the number of invalid ciphertexts and achieve secure deduplication, Metaverse healthcare ciphertext validity and equivalence detection are also provided in this scheme. Furthermore, a novel attribute-based re-encryption is proposed for authority delegation after deduplication. Finally, the experiment simulated on the PBC library shows that the proposed scheme possesses good performance. The freshness of Metaverse healthcare data and the utilization of the medical center's private server are ensured in this paper.

Original languageEnglish
Pages (from-to)299-310
Number of pages12
JournalFuture Generation Computer Systems
Publication statusPublished - 2023 Mar

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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