Cited by 405Blockchain Technology Applications and SecurityCloud Data Security SolutionsBlockchain Technology in Education and Learning

Privacy-friendly platform for healthcare data in cloud based on blockchain environment

Omar, Abdullah Al, Bhuiyan, Md Zakirul Alam, Basu, Anirban, Kiyomoto, Shinsaku, Rahman, Mohammad Shahriar·2019·Future Generation Computer Systems

Integrity signals

Registry

Crossref · 10.1016/j.future.2018.12.044

Cites

31 of 31 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Scholars have focused on storage and preservation of sensitive data from sources such as medical devices and medical insurance.

    “With the increasing inter-institutional adoption of blockchain, scholars have also focused on the issue of storage and preservation of sensitive data (Al Omar et al., 2019) from different sources such as medical devices (Firdaus et al., 2018), and medical insurance (Zhou et al., 2018).”
  • A few studies directed attention to facilitating cross-institutional data sharing and improving efficiency and flexibility of data sharing.

    “A few studies have also directed attention to the facilitation of crossinstitutional data sharing (Al Omar et al., 2019), and improvements in efficiency as well as flexibility of data sharing (Shen et al., 2019).”
  • Few reviewed studies acknowledged the need for regulatory compliance or standards and goals for compliance requirements.

    “Our review suggests that few studies have acknowledged the need for regulatory compliance (Yue et al., 2016) or even the standards and goals for compliance requirements (Zhang & Lin, 2018;Al Omar et al., 2019;Li et al., 2019).”
  • Extant research indicates costs including linear increase in protocol costs based on entity characteristics, increased operational overhead and access latency, and transaction/execution costs based on string length and size.

    “Additionally, other costs indicated as constraints and limitations in the extant research include the linear increase in protocol costs contingent upon the characteristics and attributes of the involved entities, such as patients (Guo et al., 2018), increased operational overhead (for the patient) and access latency (for the requester) (Shen et al., 2019), and the transaction and execution costs”
  • The weakness of Ref. [90] is that a smart contract for managing data storage has not been implemented.

    “The weakness of the article is that a smart contract for managing data storage has not been implemented.”

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Authors
Omar, A. A., Bhuiyan, M. Z. A., Basu, A., Kiyomoto, S., & Rahman, M. S.
Affiliations
  • University of Asia Pacific (BD)
  • Fordham University (US)
  • University of Sussex (GB)
  • KDDI Research (Japan) (JP)
  • University of Liberal Arts Bangladesh (BD)
Corresponding author
  • Bhuiyan, Md Zakirul Alam
  • Rahman, Mohammad Shahriar
Venue
Future Generation Computer Systems
Publisher
Elsevier BV
Published
2019-06
Volume
95
Pages
511-521
ISSN
0167-739X (ISSN-L)
OpenAlex
W2910972514
Cited by
404
References
31
Citations by year
2026: 14 · 2025: 31 · 2024: 61 · 2023: 70 · 2022: 66 · 2021: 89 · 2020: 58 · 2019: 14 · 2018: 1
FWCI
70.62
Type
journal article
Language
en
Open access
closed
Locations
Future Generation Computer Systems (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
healthcare data privacy, blockchain, cloud security, decentralized storage, peer-to-peer networks, smart contracts, data encryption, pseudonymity, data integrity

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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.

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