{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T13:04:30Z","timestamp":1771679070681,"version":"3.50.1"},"reference-count":34,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T00:00:00Z","timestamp":1677456000000},"content-version":"vor","delay-in-days":57,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072369"],"award-info":[{"award-number":["62072369"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072371"],"award-info":[{"award-number":["62072371"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Projects of Shaanxi Province","doi-asserted-by":"publisher","award":["2021ZDLGY06-02"],"award-info":[{"award-number":["2021ZDLGY06-02"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Projects of Shaanxi Province","doi-asserted-by":"publisher","award":["2020ZDLGY08-04"],"award-info":[{"award-number":["2020ZDLGY08-04"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008780","name":"Xi'an University of Posts and Telecommunications","doi-asserted-by":"publisher","award":["CXJJZL2021025"],"award-info":[{"award-number":["CXJJZL2021025"]}],"id":[{"id":"10.13039\/501100008780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008780","name":"Xi'an University of Posts and Telecommunications","doi-asserted-by":"publisher","award":["CXJJYL2021075"],"award-info":[{"award-number":["CXJJYL2021075"]}],"id":[{"id":"10.13039\/501100008780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Systems"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:p>The rapid development of smart healthcare system in the Internet of Things (IoT) has made the early detection of many chronic diseases more convenient, quick, and economical. However, when healthcare organizations collect users\u2019 health data through deployed IoT devices, there are issues of compromising users\u2019 privacy. In view of this situation, this paper introduces federated learning technology to solve the problem of data security. In this paper, we consider the two main problems of federated learning applications in IoT smart healthcare system: (1) how to reduce the time overhead of system running and (2) how to authenticate that the user device uploading data is deployed by the system itself. To solve the above problems, we propose the first federated learning scheme based on full dynamic secret sharing. First, we use a two\u2010mask protocol to keep the user\u2019s local model parameters confidential during federated learning. Then, based on homogeneous linear recursive equation, homomorphic hash function, and elliptic curve cryptosystem, the full dynamic secret sharing and user identity authentication are realized. In addition, our scheme allows users to join or quit during training. Finally, we have carried out simulation test on this scheme. The experimental results show that the efficiency of our scheme is improved by about 60% on average in the case of no user dropping and by about 30% in the case of some users dropping.<\/jats:p>","DOI":"10.1155\/2023\/8017489","type":"journal-article","created":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T03:05:07Z","timestamp":1677553507000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Secure and Efficient Smart Healthcare System Based on Federated Learning"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1679-6862","authenticated-orcid":false,"given":"Wei","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5764-3272","authenticated-orcid":false,"given":"Yinghui","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2305-6870","authenticated-orcid":false,"given":"Gang","family":"Han","sequence":"additional","affiliation":[]},{"given":"Jin","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Cui","sequence":"additional","affiliation":[]},{"given":"Dong","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"e_1_2_12_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/jsac.2009.090502"},{"key":"e_1_2_12_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/mwc.2012.6393513"},{"key":"e_1_2_12_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s42452-019-1925-y"},{"key":"e_1_2_12_4_2","doi-asserted-by":"crossref","unstructured":"UkilA. 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