{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:30:45Z","timestamp":1774449045866,"version":"3.50.1"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24B20182"],"award-info":[{"award-number":["U24B20182"]}],"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":["62122066"],"award-info":[{"award-number":["62122066"]}],"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":["62472158"],"award-info":[{"award-number":["62472158"]}],"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":["62102337"],"award-info":[{"award-number":["62102337"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&amp;D Program of China","award":["2021ZD0112803"],"award-info":[{"award-number":["2021ZD0112803"]}]},{"name":"Key R&amp;D Program of Zhejiang","award":["2024C01164"],"award-info":[{"award-number":["2024C01164"]}]},{"name":"Key R&amp;D Program of Zhejiang","award":["2022C01018"],"award-info":[{"award-number":["2022C01018"]}]},{"name":"Young Elite Scientists Sponsorship Program by CAST","award":["2023QNRC001"],"award-info":[{"award-number":["2023QNRC001"]}]},{"DOI":"10.13039\/501100004761","name":"Natural Science Foundation of Hainan Province","doi-asserted-by":"publisher","award":["2023JJ40174"],"award-info":[{"award-number":["2023JJ40174"]}],"id":[{"id":"10.13039\/501100004761","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Innovation Program of Hunan Province","award":["2024RC3102"],"award-info":[{"award-number":["2024RC3102"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62432004"],"award-info":[{"award-number":["62432004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Dependable and Secure Comput."],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1109\/tdsc.2025.3541306","type":"journal-article","created":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T13:53:35Z","timestamp":1739454815000},"page":"3795-3807","source":"Crossref","is-referenced-by-count":2,"title":["Towards Fair Federated Learning via Unbiased Feature Aggregation"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0093-2951","authenticated-orcid":false,"given":"Zeqing","family":"He","sequence":"first","affiliation":[{"name":"State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5804-3279","authenticated-orcid":false,"given":"Zhibo","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8632-7757","authenticated-orcid":false,"given":"Xiaowei","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6221-8142","authenticated-orcid":false,"given":"Peng","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2782-183X","authenticated-orcid":false,"given":"Ju","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1969-2591","authenticated-orcid":false,"given":"Kui","family":"Ren","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/9781680837896"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2018.01.007"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_17"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155494"},{"key":"ref8","article-title":"Achieving linear speedup with partial worker participation in non-IID federated learning","author":"Yang","year":"2021"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00983"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00990"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134012"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00029"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2018.00057"},{"key":"ref14","first-page":"1605","article-title":"Local model poisoning attacks to Byzantine-Robust federated learning","volume-title":"Proc. 29th USENIX Secur. Symp.","author":"Fang"},{"key":"ref15","first-page":"12878","article-title":"Data-free knowledge distillation for heterogeneous federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhu"},{"key":"ref16","first-page":"21394","article-title":"Personalized federated learning with Moreau envelopes","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Dinh"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796935"},{"key":"ref18","first-page":"3581","article-title":"Federated learning with buffered asynchronous aggregation","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Nguyen"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM52122.2024.10621333"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2023.3317870"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.23919\/cje.2022.00.031"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM52122.2024.10621090"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2945367"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2929409"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011544"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00842"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467281"},{"key":"ref28","article-title":"FedMD: Heterogenous federated learning via model distillation","author":"Li","year":"2019"},{"key":"ref29","article-title":"HeteroFL: Computation and communication efficient federated learning for heterogeneous clients","author":"Diao","year":"2020"},{"key":"ref30","article-title":"Efficient split-mix federated learning for on-demand and in-situ customization","author":"Hong","year":"2022"},{"key":"ref31","first-page":"2351","article-title":"Ensemble distillation for robust model fusion in federated learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Lin"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tit.2022.3192506"},{"key":"ref33","first-page":"5311","article-title":"Learning from history for byzantine robust optimization","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Karimireddy"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i6.25911"},{"key":"ref35","first-page":"6357","article-title":"Ditto: Fair and robust federated learning through personalization","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref36","article-title":"Fair resource allocation in federated learning","author":"Li","year":"2019"},{"key":"ref37","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref38","article-title":"FitNets: Hints for thin deep nets","author":"Romero","year":"2014"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00201"},{"key":"ref40","article-title":"Avoiding discrimination through causal reasoning","author":"Kilbertus","year":"2017"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3106237.3106277"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052660"},{"key":"ref43","first-page":"3323","article-title":"Equality of opportunity in supervised learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Hardt"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0463-8"},{"key":"ref46","article-title":"FairBatch: Batch selection for model fairness","author":"Roh","year":"2020"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00894"}],"container-title":["IEEE Transactions on Dependable and Secure Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8858\/11077775\/10884063.pdf?arnumber=10884063","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T17:45:24Z","timestamp":1752515124000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10884063\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":47,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tdsc.2025.3541306","relation":{},"ISSN":["1545-5971","1941-0018","2160-9209"],"issn-type":[{"value":"1545-5971","type":"print"},{"value":"1941-0018","type":"electronic"},{"value":"2160-9209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7]]}}}