Decentralized Privacy Protection of IoTs Using Blockchain-Enabled Federated Learning Qu, Y, Gao, Longxiang, Yu, S and Xiang, Yong 2022, Decentralized Privacy Protection of IoTs Using Blockchain-Enabled Federated Learning. In Qu, Y, Gao, L, Yu, S and Xiang, Y (ed), Privacy Preservation in IoT: Machine Learning Approaches: A Comprehensive Survey and Use Cases, Springer Nature, Singapore, pp.19-48, doi: 10.1007/978-981-19-1797-4_3. Title Decentralized Privacy Protection of IoTs Using Blockchain-Enabled Federated Learning Author(s) Qu, Y Gao, Longxiang orcid.org/0000-0002-3026-7537 Yu, S Xiang, Yong orcid.org/0000-0003-3545-7863 Title of book Privacy Preservation in IoT: Machine Learning Approaches: A Comprehensive Survey and Use Cases Editor(s) Qu, Y Gao, L Yu, S Xiang, Y Publication date 2022 Series SpringerBriefs in Computer Science Chapter number 3 Total chapters 7 Start page 19 End page 48 Total pages 28 Publisher Springer Nature Place of Publication Singapore ISBN 9789811917967 ISSN 2191-5768 2191-5776 Language eng DOI 10.1007/978-981-19-1797-4_3 HERDC Research category B1 Book chapter Persistent URL http://hdl.handle.net/10536/DRO/DU:30168867 Document type: Book Chapter Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 23 May 2022, 08:28:49 EST Mon, 23 May 2022, 16:10:52 EST Tue, 21 Jun 2022, 16:14:46 EST Fri, 24 Jun 2022, 07:37:10 EST Fri, 24 Jun 2022, 13:48:03 EST Fri, 24 Jun 2022, 13:50:34 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 20 Abstract Views  -  Detailed Statistics Created: Mon, 23 May 2022, 08:28:49 EST