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Towards design and implementation of security and privacy framework for Internet of Medical Things (IoMT) by leveraging blockchain and IPFS technology
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“In the IoT-based healthcare system, several attacks can hamper the total loss of the system.”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [199]
In the citing paper
“Preference, side-channel attack [198], data duplication using the tag, physical hampering of the sensor devices, or sensor tracking are some of the attacks that may cause issues in the perception layer [199].”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [199]
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Metadata
- Authors
- Kumar, R., & Tripathi, R.
- Affiliations
- National Institute of Technology Raipur (IN)
- Corresponding author
- Kumar, Randhir
- Venue
- The Journal of Supercomputing
- Published
- 2021-01-12
- Volume
- 77
- Issue
- 8
- Pages
- 7916-7955
- ISSN
- 0920-8542 (ISSN-L)
- 1573-0484
- OpenAlex
- W3120480193
- Cited by
- 177
- References
- 56
- Citations by year
- 2026: 6 · 2025: 33 · 2024: 41 · 2023: 50 · 2022: 37 · 2021: 10
- FWCI
- 31.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Supercomputing (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
- Internet of Medical Things, healthcare data security, patient privacy, consortium blockchain, smart contracts, IPFS, distributed storage, patient authentication
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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