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Lightweight certificateless privacy-preserving integrity verification with conditional anonymity for cloud-assisted medical cyber–physical systems

  • Jie Zhao
  • , Yifeng Zheng
  • , Hejiao Huang*
  • , Jing Wang
  • , Xiaojun Zhang
  • , Daojing He
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Huazhong University of Science and Technology
  • Southwest Petroleum University China

Research output: Contribution to journalArticlepeer-review

Abstract

Cloud-assisted medical cyber–physical systems (MCPSs) leverage the power of cloud computing for scalable storage and management of outsourced medical data. Based on the crucial outsourced medical data, guardians could know patient's health condition timely, doctors can make accurate diagnoses of patients, and medical research centers could also conduct medical big data analysis. However, medical data is highly sensitive and demands strong protection. Meanwhile, the integrity of outsourced medical data is vulnerable to hardware failures, software bugs or human errors. To date, a large number of data privacy-preserving integrity auditing schemes have been presented, but most of them suffer from the burden of complex public key certificate management or the key escrow problem of identity-based cryptography. In this paper, we propose a lightweight certificateless privacy-preserving integrity verification scheme (LCPPIV) with conditional anonymity for cloud-assisted MCPSs by developing an elliptic-curve digital signature and a key exchange mechanism, which can achieve the functionalities of medical data privacy protection, integrity verification of outsourced medical data, conditional anonymity, batch auditing, and secure compensation mechanism, simultaneously. Theoretical security analysis demonstrates that our scheme is provably secure in the random oracle model, with resistance to the public key replacement attack, malicious-but-passive-KGC attack, and response auditing proofs forgery. The performance evaluations indicate that LCPPIV is much more practical for cloud-assisted MCPSs compared with state-of-art data auditing schemes.

Original languageEnglish
Article number102860
JournalJournal of Systems Architecture
Volume138
DOIs
StatePublished - May 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cloud computing
  • Compensation mechanism
  • Conditional anonymity
  • Data integrity auditing
  • Medical cyber–physical systems

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