{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T07:42:21Z","timestamp":1774942941927,"version":"3.50.1"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T00:00:00Z","timestamp":1638316800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS-1908807"],"award-info":[{"award-number":["CNS-1908807"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["AST-2037838"],"award-info":[{"award-number":["AST-2037838"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["ECCS-2030251"],"award-info":[{"award-number":["ECCS-2030251"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Select. Areas Commun."],"published-print":{"date-parts":[[2021,12]]},"DOI":"10.1109\/jsac.2021.3118423","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T20:10:13Z","timestamp":1633983013000},"page":"3790-3804","source":"Crossref","is-referenced-by-count":53,"title":["Faithful Edge Federated Learning: Scalability and Privacy"],"prefix":"10.1109","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4893-6946","authenticated-orcid":false,"given":"Meng","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8035-484X","authenticated-orcid":false,"given":"Ermin","family":"Wei","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1861-6722","authenticated-orcid":false,"given":"Randall","family":"Berry","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3118354"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3036944"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2020.2994639"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.2971981"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2940820"},{"key":"ref30","first-page":"8927","article-title":"Collaborative machine learning with incentive-aware model rewards","author":"sim","year":"2020","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3375627.3375840"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2020.2987774"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/LNET.2019.2947144"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2967772"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2985694"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2019.2952332"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00094"},{"key":"ref2","author":"kelly","year":"2015","journal-title":"Internet of Things data to top 1 6 zettabytes by 2020"},{"key":"ref1","first-page":"1","article-title":"Faithful federated learning","author":"zhang","year":"2021","journal-title":"Proc Workshop the Economics of Networks Systems and Computation (NetEcon)"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2961673"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3024629"},{"key":"ref21","article-title":"Client selection for federated learning with heterogeneous resources in mobile edge","author":"nishio","year":"2018","journal-title":"arXiv 1804 08333"},{"key":"ref24","article-title":"Federated learning on the road: Autonomous controller design for connected and autonomous vehicles","author":"zeng","year":"2021","journal-title":"arXiv 2102 03401"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3037554"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2021.3063517"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3052681"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/11681878_14"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP.2013.6736861"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3118423"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-53641-4_24"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1017\/9781108627771"},{"key":"ref10","first-page":"6885","article-title":"Provably secure federated learning against malicious clients","volume":"35","author":"cao","year":"2021","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref11","article-title":"BAFFLE: Towards resolving federated learning&#x2019;s dilemma-thwarting backdoor and inference attacks","author":"nguyen","year":"2021","journal-title":"Proc ICLR"},{"key":"ref40","author":"vazirani","year":"2007","journal-title":"Algorithmic Game Theory"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2005.843546"},{"key":"ref13","first-page":"4424","article-title":"Federated multi-task learning","author":"smith","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/357172.357176"},{"key":"ref15","article-title":"Robust aggregation for federated learning","author":"pillutla","year":"2019","journal-title":"arXiv 1912 13445"},{"key":"ref16","article-title":"Advances and open problems in federated learning","author":"kairouz","year":"2019","journal-title":"arXiv 1912 04977"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.001.1900103"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2904348"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2019.2944169"},{"key":"ref4","article-title":"Federated learning for mobile keyboard prediction","author":"hard","year":"2018","journal-title":"arXiv 1811 03604"},{"key":"ref3","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2016","journal-title":"arXiv 1602 05629"},{"key":"ref6","first-page":"1","article-title":"A hybrid approach to privacy-preserving federated learning","author":"truex","year":"2019","journal-title":"Proc 12th ACM Workshop Artif Intell Secur (AISec)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref8","first-page":"1","article-title":"Distributed learning without distress: Privacy-preserving empirical risk minimization","author":"jayaraman","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref49","article-title":"Linear convergence of gradient and proximal-gradient methods under the Polyak-?ojasiewicz condition","author":"karimi","year":"2016","journal-title":"arXiv 1608 04636"},{"key":"ref7","article-title":"Scalable private learning with PATE","author":"papernot","year":"2018","journal-title":"arXiv 1802 08908"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2945367"},{"key":"ref46","first-page":"1545","article-title":"Fast rates for regularized objectives","volume":"21","author":"sridharan","year":"2008","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref45","first-page":"831","article-title":"Principles of risk minimization for learning theory","author":"vapnik","year":"1992","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1111\/1468-0262.00296"},{"key":"ref47","first-page":"2242","article-title":"Data shapley: Equitable valuation of data for machine learning","author":"ghorbani","year":"2019","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s00446-005-0134-7"},{"key":"ref41","first-page":"261","article-title":"Distributed implementations of Vickrey-Clarke-Groves mechanisms","author":"parkes","year":"2004","journal-title":"Proc 3rd Int Joint Conf Autonomous Agents and Multiagent Systems (AAMAS)"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TCNS.2015.2489318"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1613\/jair.2500"}],"container-title":["IEEE Journal on Selected Areas in Communications"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/49\/9620733\/9567711-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/49\/9620733\/09567711.pdf?arnumber=9567711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T18:48:06Z","timestamp":1649443686000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9567711\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12]]},"references-count":55,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/jsac.2021.3118423","relation":{},"ISSN":["0733-8716","1558-0008"],"issn-type":[{"value":"0733-8716","type":"print"},{"value":"1558-0008","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12]]}}}