Next-generation cybersecurity through a blockchain-enabled federated cloud framework
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
The privacy of data is well maintained by distributed blockchain ledgers, while data owners have full control on their data shared in the network, improving the data ownership capability of sharing models.
“Further, the privacy of data is well maintained by distributed blockchain ledgers, while data owners have full control on their data shared in the network, improving the data ownership capability of sharing models [167].”
From Blockchain for 5G and beyond networks: A state of the art survey (2020) · cites this paper as [167]
The citation lists haven’t been fetched yet
References 22 · Cited by 37
- Authors
- Malomo, O. O., Rawat, D. B., & Garuba, M.
- Affiliations
- Howard University (US)
- Corresponding author
- Rawat, Danda B.
- Venue
- The Journal of Supercomputing
- Published
- 2018-05-02
- Volume
- 74
- Issue
- 10
- Pages
- 5099-5126
- ISSN
- 0920-8542 (ISSN-L)
- 1573-0484
- OpenAlex
- W2801426461
- Cited by
- 37
- References
- 22
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 8 · 2022: 5 · 2021: 6 · 2020: 8 · 2019: 6
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Supercomputing (publishedVersion)
- Funders
- Directorate for Computer and Information Science and Engineering (1405670)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Digital and Cyber Forensics
- Keywords
- blockchain, cloud federation, cyberattack detection, Dempster-Shafer theory, network traffic monitoring, cybersecurity
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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