Cited by 462Blockchain Technology Applications and SecurityInternet of Things and AIIoT and Edge/Fog Computing

An exhaustive survey on security and privacy issues in Healthcare 4.0

Hathaliya, Jigna J., Tanwar, Sudeep·2020·Computer Communications

Integrity signals

Registry

Crossref · 10.1016/j.comcom.2020.02.018

Cites

156 of 156 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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  • Medical 4.0 technologies are evolving into a patient-centred approach in which data will be provided to industry participants to develop better technology and healthcare delivery concepts.

    “These technologies are evolving into a patient-centred approach in which the data will be provided to industry participants to develop better technology and healthcare delivery concepts [28,29].”

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Authors
Hathaliya, J. J., & Tanwar, S.
Affiliations
Nirma University (IN)
Corresponding author
Tanwar, Sudeep
Venue
Computer Communications
Publisher
Elsevier BV
Published
2020-03
Volume
153
Pages
311-335
ISSN
0140-3664 (ISSN-L)
OpenAlex
W3005929894
Cited by
462
References
156
Citations by year
2026: 35 · 2025: 70 · 2024: 91 · 2023: 82 · 2022: 88 · 2021: 64 · 2020: 32
FWCI
59.28
Type
journal article
Language
en
Open access
closed
Locations
Computer Communications (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
Healthcare 4.0, healthcare data security, healthcare privacy, blockchain, cloud computing, fog computing, Internet of Things, telemedicine, electronic health records, data breaches, security taxonomy, privacy-preserving techniques

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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