The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.
The rise of “blockchain”: bibliometric analysis of blockchain study
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To avoid fraud-related activities such as double-spending attacks, the trustworthiness of the block must be checked, and the data flow should be controlled to ensure the smooth exchange of information.
“To avoid fraud-related activities such as double-spending attacks, the trustworthiness of the block must be checked, and the data flow should be controlled to ensure the smooth exchange of information [63].”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [63]
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Metadata
- Authors
- Firdaus, A., Razak, M. F. A., Feizollah, A., Hashem, I. A. T., Hazim, M., & Anuar, N. B.
- Affiliations
- Universiti Malaysia Pahang Al-Sultan Abdullah (MY)
- University of Malaya (MY)
- Corresponding author
- Razak, Mohd Faizal Ab
- Venue
- Scientometrics
- Published
- 2019-07-05
- Volume
- 120
- Issue
- 3
- Pages
- 1289-1331
- ISSN
- 0138-9130 (ISSN-L)
- 1588-2861
- OpenAlex
- W2955437544
- Cited by
- 208
- References
- 98
- Citations by year
- 2026: 11 · 2025: 27 · 2024: 43 · 2023: 33 · 2022: 36 · 2021: 35 · 2020: 18 · 2019: 5
- FWCI
- 15.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Scientometrics (publishedVersion)
- UMP Institutional Repository (Universiti Malaysia Pahang) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Funders
- Universiti Malaysia Pahang (RDU180360)
- Topics
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Keywords
- blockchain, consensus algorithms, Internet of Things security, blockchain in healthcare, data privacy, distributed databases, international research collaboration, citation analysis
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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