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Bubbles of Trust: A decentralized blockchain-based authentication system for IoT
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“Nowadays, ML-based privacy preservation is mostly used due to its efficiency [34], and the more preferable technique is federated learning (FL).”
From Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey (2023) · cites this paper as [34]
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Metadata
- Authors
- Hammi, M. T., Hammi, B., Bellot, P., & Serhrouchni, A.
- Affiliations
- ParisTech (FR)
- Corresponding author
- Hammi, Badis
- ORCID
- Hammi, Badis
- Venue
- Computers & Security
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 78
- Pages
- 126-142
- ISSN
- 0167-4048 (ISSN-L)
- OpenAlex
- W2810652557
- Cited by
- 691
- References
- 56
- Citations by year
- 2026: 23 · 2025: 66 · 2024: 69 · 2023: 101 · 2022: 130 · 2021: 127 · 2020: 100 · 2019: 66 · 2018: 9
- FWCI
- 121.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Security (publishedVersion)
- HAL (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Authentication Protocols Security
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- Internet of Things security, decentralized authentication, blockchain, device authentication, data integrity, Ethereum, IoT device identification
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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