A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing Article Swipe
Ervin Moore
,
Ahmed Imteaj
,
Shabnam Rezapour
,
M. Hadi Amini
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2303.13727
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2303.13727
Federated Learning (FL) has gained widespread popularity in recent years due to the fast booming of advanced machine learning and artificial intelligence along with emerging security and privacy threats. FL enables efficient model generation from local data storage of the edge devices without revealing the sensitive data to any entities. While this paradigm partly mitigates the privacy issues of users' sensitive data, the performance of the FL process can be threatened and reached a bottleneck due to the growing cyber threats and privacy violation techniques. To expedite the proliferation of FL process, the integration of blockchain for FL environments has drawn prolific attention from the people of academia and industry. Blockchain has the potential to prevent security and privacy threats with its decentralization, immutability, consensus, and transparency characteristic. However, if the blockchain mechanism requires costly computational resources, then the resource-constrained FL clients cannot be involved in the training. Considering that, this survey focuses on reviewing the challenges, solutions, and future directions for the successful deployment of blockchain in resource-constrained FL environments. We comprehensively review variant blockchain mechanisms that are suitable for FL process and discuss their trade-offs for a limited resource budget. Further, we extensively analyze the cyber threats that could be observed in a resource-constrained FL environment, and how blockchain can play a key role to block those cyber attacks. To this end, we highlight some potential solutions towards the coupling of blockchain and federated learning that can offer high levels of reliability, data privacy, and distributed computing performance.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2303.13727
- https://arxiv.org/pdf/2303.13727
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4361191951
All OpenAlex metadata
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https://openalex.org/W4361191951Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2303.13727Digital Object Identifier
- Title
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A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained ComputingWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-03-24Full publication date if available
- Authors
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Ervin Moore, Ahmed Imteaj, Shabnam Rezapour, M. Hadi AminiList of authors in order
- Landing page
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https://arxiv.org/abs/2303.13727Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2303.13727Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2303.13727Direct OA link when available
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Blockchain, Computer science, Decentralization, Bottleneck, Computer security, Transparency (behavior), Popularity, Cryptocurrency, Information privacy, Resource (disambiguation), Computer network, Political science, Embedded system, Law, Psychology, Social psychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.threats. | 28 |
| abstract_inverted_index.Federated | 0 |
| abstract_inverted_index.attention | 102 |
| abstract_inverted_index.computing | 248 |
| abstract_inverted_index.efficient | 31 |
| abstract_inverted_index.entities. | 49 |
| abstract_inverted_index.federated | 235 |
| abstract_inverted_index.highlight | 225 |
| abstract_inverted_index.industry. | 109 |
| abstract_inverted_index.mechanism | 132 |
| abstract_inverted_index.mitigates | 54 |
| abstract_inverted_index.potential | 113, 227 |
| abstract_inverted_index.revealing | 43 |
| abstract_inverted_index.reviewing | 154 |
| abstract_inverted_index.sensitive | 45, 60 |
| abstract_inverted_index.solutions | 228 |
| abstract_inverted_index.training. | 147 |
| abstract_inverted_index.violation | 83 |
| abstract_inverted_index.Blockchain | 110 |
| abstract_inverted_index.artificial | 20 |
| abstract_inverted_index.blockchain | 95, 131, 166, 175, 210, 233 |
| abstract_inverted_index.bottleneck | 74 |
| abstract_inverted_index.consensus, | 124 |
| abstract_inverted_index.deployment | 164 |
| abstract_inverted_index.directions | 160 |
| abstract_inverted_index.generation | 33 |
| abstract_inverted_index.mechanisms | 176 |
| abstract_inverted_index.popularity | 6 |
| abstract_inverted_index.resources, | 136 |
| abstract_inverted_index.solutions, | 157 |
| abstract_inverted_index.successful | 163 |
| abstract_inverted_index.threatened | 70 |
| abstract_inverted_index.trade-offs | 186 |
| abstract_inverted_index.widespread | 5 |
| abstract_inverted_index.Considering | 148 |
| abstract_inverted_index.challenges, | 156 |
| abstract_inverted_index.distributed | 247 |
| abstract_inverted_index.extensively | 194 |
| abstract_inverted_index.integration | 93 |
| abstract_inverted_index.performance | 63 |
| abstract_inverted_index.techniques. | 84 |
| abstract_inverted_index.environment, | 207 |
| abstract_inverted_index.environments | 98 |
| abstract_inverted_index.intelligence | 21 |
| abstract_inverted_index.performance. | 249 |
| abstract_inverted_index.reliability, | 243 |
| abstract_inverted_index.transparency | 126 |
| abstract_inverted_index.computational | 135 |
| abstract_inverted_index.environments. | 170 |
| abstract_inverted_index.immutability, | 123 |
| abstract_inverted_index.proliferation | 88 |
| abstract_inverted_index.characteristic. | 127 |
| abstract_inverted_index.comprehensively | 172 |
| abstract_inverted_index.decentralization, | 122 |
| abstract_inverted_index.resource-constrained | 139, 168, 205 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |