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A Blockchain-Based Federated Learning Method for Smart Healthcare
The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and bloc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635913/ https://www.ncbi.nlm.nih.gov/pubmed/34868289 http://dx.doi.org/10.1155/2021/4376418 |
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author | Chang, Yuxia Fang, Chen Sun, Wenzhuo |
author_facet | Chang, Yuxia Fang, Chen Sun, Wenzhuo |
author_sort | Chang, Yuxia |
collection | PubMed |
description | The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and blockchain, has become a feasible solution for these issues. In this paper, we present a blockchain-based federated learning method for smart healthcare in which the edge nodes maintain the blockchain to resist a single point of failure and MIoT devices implement the federated learning to make full of the distributed clinical data. In particular, we design an adaptive differential privacy algorithm to protect data privacy and gradient verification-based consensus protocol to detect poisoning attacks. We compare our method with two similar methods on a real-world diabetes dataset. Promising experimental results show that our method can achieve high model accuracy in acceptable running time while also showing good performance in reducing the privacy budget consumption and resisting poisoning attacks. |
format | Online Article Text |
id | pubmed-8635913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-86359132021-12-02 A Blockchain-Based Federated Learning Method for Smart Healthcare Chang, Yuxia Fang, Chen Sun, Wenzhuo Comput Intell Neurosci Research Article The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and blockchain, has become a feasible solution for these issues. In this paper, we present a blockchain-based federated learning method for smart healthcare in which the edge nodes maintain the blockchain to resist a single point of failure and MIoT devices implement the federated learning to make full of the distributed clinical data. In particular, we design an adaptive differential privacy algorithm to protect data privacy and gradient verification-based consensus protocol to detect poisoning attacks. We compare our method with two similar methods on a real-world diabetes dataset. Promising experimental results show that our method can achieve high model accuracy in acceptable running time while also showing good performance in reducing the privacy budget consumption and resisting poisoning attacks. Hindawi 2021-11-24 /pmc/articles/PMC8635913/ /pubmed/34868289 http://dx.doi.org/10.1155/2021/4376418 Text en Copyright © 2021 Yuxia Chang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chang, Yuxia Fang, Chen Sun, Wenzhuo A Blockchain-Based Federated Learning Method for Smart Healthcare |
title | A Blockchain-Based Federated Learning Method for Smart Healthcare |
title_full | A Blockchain-Based Federated Learning Method for Smart Healthcare |
title_fullStr | A Blockchain-Based Federated Learning Method for Smart Healthcare |
title_full_unstemmed | A Blockchain-Based Federated Learning Method for Smart Healthcare |
title_short | A Blockchain-Based Federated Learning Method for Smart Healthcare |
title_sort | blockchain-based federated learning method for smart healthcare |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635913/ https://www.ncbi.nlm.nih.gov/pubmed/34868289 http://dx.doi.org/10.1155/2021/4376418 |
work_keys_str_mv | AT changyuxia ablockchainbasedfederatedlearningmethodforsmarthealthcare AT fangchen ablockchainbasedfederatedlearningmethodforsmarthealthcare AT sunwenzhuo ablockchainbasedfederatedlearningmethodforsmarthealthcare AT changyuxia blockchainbasedfederatedlearningmethodforsmarthealthcare AT fangchen blockchainbasedfederatedlearningmethodforsmarthealthcare AT sunwenzhuo blockchainbasedfederatedlearningmethodforsmarthealthcare |