Evidence map›Paper›PMID 39987251›Full record

ArticleScientific reports2025

Provably secure and lightweight blockchain based cross hospital authentication scheme for IoMT-based healthcare.

Qi Xie, Zixuan Ding

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qi XieKey Laboratory of Cryptography of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121, China. qixie68@126.com.
Zixuan DingCollege of Cryptology and Cyber Science, Nankai University, Tianjin, 300350, China.

Funding

Hangzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China LHZSZ24F020002National Natural Science Foundation of China U21A20466
6 · The paper itself

Abstract

Portable devices and sensors-based Internet of Medical Things (IoMT) healthcare can remotely detect patients' physiological data and provide first-class healthcare services. However, the high privacy and sensitivity of medical data make IoMT healthcare systems vulnerable to various attacks. While numerous authentication protocols have been introduced in recent years to guarantee authorized access, these schemes continue to face challenges such as privacy disclosure, untraceability of malicious behavior, insufficient cross-hospital access, and concerns related to single points of failure and trust. To address these issues, we propose a Double Anonymity Strategy to hide identities between doctors and the patients while allowing the authorized party to track their malicious behavior, enhance users' privacy and track malicious users. Our approach leverages the advantages of blockchain, such as decentralization, and replaces trusted third parties with smart contracts for efficient and automatic identity authentication. Additionally, we introduce a cross-hospital authentication scheme that incorporates three-factor secrecy, ensuring that even if any two of the three factors (device, biometric information and password) are compromised, the security of the proposed scheme will not be affected. The security of our scheme is formally proven under the random oracle model, which formally measures that the probability of an adversary breaking the scheme is negligible. We also provide informal security analysis showing that our scheme prevents privacy breaches, achieves decentralization, and addresses existing various attacks. Furthermore, through simulation of the proposed scheme and comparison with related works, we demonstrate that our scheme achieves 23% to 87% reduction in computational cost while maintaining higher security properties.

Indexed as

BlockchainComputer SecurityInternet of ThingsAlgorithmsConfidentialityHospitalsHumansPrivacyAuthentication protocolBlockchainCross-hospitalDecentralizationHealthcareInternet of Medical Things

Identifiers

PMID39987251
PMCPMC11846994

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.