{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T07:56:25Z","timestamp":1773388585646,"version":"3.50.1"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"20","license":[{"start":{"date-parts":[[2023,10,15]],"date-time":"2023-10-15T00:00:00Z","timestamp":1697328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,15]],"date-time":"2023-10-15T00:00:00Z","timestamp":1697328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,15]],"date-time":"2023-10-15T00:00:00Z","timestamp":1697328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFB2100100"],"award-info":[{"award-number":["2018YFB2100100"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2023,10,15]]},"DOI":"10.1109\/jiot.2023.3279830","type":"journal-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T17:57:20Z","timestamp":1685037440000},"page":"18364-18374","source":"Crossref","is-referenced-by-count":18,"title":["Privacy-Preserving Federal Learning Chain for Internet of Things"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0193-9463","authenticated-orcid":false,"given":"Yihang","family":"Xu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1829-4719","authenticated-orcid":false,"given":"Yuxing","family":"Mao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China"}]},{"given":"Simou","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China"}]},{"given":"Jian","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3270-6556","authenticated-orcid":false,"given":"Xueshuo","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Trustless machine learning contracts; evaluating and exchanging machine learning models on the Ethereum blockchain","author":"kurtulmus","year":"2018","journal-title":"arXiv 1802 10185"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/2991079.2991125"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2812239"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom\/BigDataSE.2019.00057"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2020.2975911"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/Blockchain.2019.00057"},{"key":"ref31","year":"2023","journal-title":"Microsoft SEAL (release 4 1)"},{"key":"ref30","first-page":"4424","article-title":"Federated multi-task learning","author":"smith","year":"2017","journal-title":"Proc NeurIPS"},{"key":"ref11","article-title":"Bitcoin: A peer-to-peer electronic cash system","author":"nakamoto","year":"2008"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICPADS47876.2019.00042"},{"key":"ref10","first-page":"1","article-title":"A privacy-preserving asynchronous averaging algorithm based on Shamir&#x2019;s secret sharing","author":"li","year":"2019","journal-title":"Proc IEEE 27th Eur Signal Process Conf (EUSIPCO)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3072611"},{"key":"ref1","article-title":"Federated optimization: Distributed machine learning for on-device intelligence","author":"konecn\u00fd","year":"2016","journal-title":"arXiv 1610 02527"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2987843"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3022911"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2019.2921755"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70694-8_15"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-22792-9_29"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2018.2794611"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2019.8861593"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1536414.1536440"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03459-4"},{"key":"ref28","article-title":"Federated learning of deep networks using model averaging","author":"mcmahan","year":"2016","journal-title":"arXiv 1602 05629"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2015INP0020"},{"key":"ref29","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2016","journal-title":"arXiv 1602 05629"},{"key":"ref8","first-page":"1","article-title":"Deep leakage from gradients","volume":"32","author":"zhu","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref7","article-title":"iDLG: Improved deep leakage from gradients","author":"zhao","year":"2020","journal-title":"arXiv 2001 02610"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2017.04.021"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3039359"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00029"},{"key":"ref5","first-page":"1","article-title":"Federated learning: Strategies for improving communication efficiency","author":"kone?n\u00fd","year":"2016","journal-title":"Proc NIPS Workshop Private Multi-Party Mach Learn"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488907\/10269651\/10136376.pdf?arnumber=10136376","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T18:22:22Z","timestamp":1698085342000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10136376\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,15]]},"references-count":35,"journal-issue":{"issue":"20"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2023.3279830","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,15]]}}}