{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T04:49:11Z","timestamp":1782362951080,"version":"3.54.5"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"14","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2023YFB3107500"],"award-info":[{"award-number":["2023YFB3107500"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62220106004"],"award-info":[{"award-number":["62220106004"]}],"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":["62402358"],"award-info":[{"award-number":["62402358"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Technology Innovation Leading Program of Shaanxi","award":["2022KXJ-093"],"award-info":[{"award-number":["2022KXJ-093"]}]},{"name":"Technology Innovation Leading Program of Shaanxi","award":["2023KXJ-033"],"award-info":[{"award-number":["2023KXJ-033"]}]},{"name":"Innovation Capability Support Program of Shaanxi","award":["2023-CX-TD-02"],"award-info":[{"award-number":["2023-CX-TD-02"]}]},{"name":"Key Research and Development Program of Shandong Province of China","award":["2023CXPT056"],"award-info":[{"award-number":["2023CXPT056"]}]},{"name":"Young Talent Fund of Association for Science and Technology in Shaanxi, China","award":["20240138"],"award-info":[{"award-number":["20240138"]}]},{"name":"Open Topics from the Lion Rock Labs of Cyberspace Security","award":["LRL24004"],"award-info":[{"award-number":["LRL24004"]}]},{"name":"Open Project Foundation of Shaanxi Key Laboratory of Information Communication Network and Security","award":["ICNS202301"],"award-info":[{"award-number":["ICNS202301"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZDRC2202"],"award-info":[{"award-number":["ZDRC2202"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["KYFZ25005"],"award-info":[{"award-number":["KYFZ25005"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University","award":["YJSJ25012"],"award-info":[{"award-number":["YJSJ25012"]}]},{"name":"Double First-Class Overseas Research Project of Xidian University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,7,15]]},"DOI":"10.1109\/jiot.2025.3568443","type":"journal-article","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T14:01:51Z","timestamp":1746799311000},"page":"29073-29088","source":"Crossref","is-referenced-by-count":4,"title":["Byzantine-Robust Federated Learning Framework via a Server-Client Defense Mechanisms"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6616-265X","authenticated-orcid":false,"given":"Anxiao","family":"Song","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5739-8038","authenticated-orcid":false,"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7948-819X","authenticated-orcid":false,"given":"Ke","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Institute of Science Tokyo, Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7677-6193","authenticated-orcid":false,"given":"Xinghui","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8448-705X","authenticated-orcid":false,"given":"Yulong","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2024.3372634"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3451359"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2024.3459037"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583347"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/s20216230"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i11.21505"},{"key":"ref7","first-page":"634","article-title":"Analyzing federated learning through an adversarial lens","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bhagoji"},{"key":"ref8","first-page":"25044","article-title":"Collaborative learning in the jungle (decentralized, Byzantine, heterogeneous, asynchronous and nonconvex learning)","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst.","volume":"34","author":"El-Mhamdi"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SP46214.2022.9833647"},{"key":"ref10","first-page":"1","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. 31st Conf. Neural Inf. Process. Syst.","volume":"30","author":"Blanchard"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3116976"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24434"},{"key":"ref13","first-page":"12613","article-title":"FL-WBC: Enhancing robustness against model poisoning attacks in federated learning from a client perspective","volume-title":"Proc. 35th Conf. Neural Inf. Process. Syst.","volume":"34","author":"Sun"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20903"},{"key":"ref15","first-page":"43158","article-title":"LeadFL: Client self-defense against model poisoning in federated learning","volume-title":"Proc. 40th Int. Conf. Mach. Learn.","author":"Zhu"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111660"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3376255"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2023.01.019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.33969\/J-NaNA.2024.040104"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2023.3257510"},{"key":"ref21","article-title":"Poisoning attacks against support vector machines","author":"Biggio","year":"2012","journal-title":"arXiv:1206.6389"},{"key":"ref22","first-page":"35007","article-title":"Learning to attack federated learning: A model-based reinforcement learning attack framework","volume-title":"Proc. 36th Conf. Neural Inf. Process. Syst.","volume":"35","author":"Li"},{"key":"ref23","first-page":"5650","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yin"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24498"},{"issue":"6","key":"ref25","first-page":"536","article-title":"A survey: Linear and nonlinear PCA based face recognition techniques","volume":"10","author":"Shah","year":"2013","journal-title":"Int. Arab J. Inf. Technol."},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2022.23054"},{"key":"ref27","first-page":"9489","article-title":"Personalized federated learning using hypernetworks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Shamsian"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2014.09.064"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/362342.362367"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/BF02241270"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2013.143"},{"key":"ref32","first-page":"2351","article-title":"Ensemble distillation for robust model fusion in federated learning","volume-title":"Proc. 34th Conf. Neural Inf. Process. Syst.","volume":"33","author":"Lin"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10661"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3272334"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3352415"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref37","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref39","first-page":"560","article-title":"signSGD: Compressed optimisation for non-convex problems","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bernstein"},{"key":"ref40","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Hsu","year":"2019","journal-title":"arXiv:1909.06335"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011544"},{"key":"ref42","first-page":"1605","article-title":"Local model poisoning attacks to Byzantine-robust federated learning","volume-title":"Proc. 29th USENIX Secur. Symp. (USENIX Secur.)","author":"Fang"},{"key":"ref43","first-page":"8635","article-title":"A little is enough: Circumventing defenses for distributed learning","volume-title":"Proc. 33rd Conf. Neural Inf. Process. Syst.","volume":"32","author":"Baruch"},{"key":"ref44","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/SPW59333.2023.00012"},{"key":"ref46","first-page":"493","article-title":"BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning","volume-title":"Proc. USENIX Annu. Techn. Conf. (USENIX ATC)","author":"Zhang"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-020-00780-4"},{"key":"ref48","first-page":"1","article-title":"On the convergence of FedAvg on non-IID data","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1017\/9781108627771"},{"key":"ref50","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proc. Mach. Learn. Syst.","author":"Li"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/3154503"},{"key":"ref52","article-title":"Introduction to the non-asymptotic analysis of random matrices","author":"Vershynin","year":"2010","journal-title":"arXiv:1011.3027"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/11074249\/10994501.pdf?arnumber=10994501","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T17:49:15Z","timestamp":1752169755000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10994501\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,15]]},"references-count":52,"journal-issue":{"issue":"14"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2025.3568443","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,15]]}}}