{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T18:46:42Z","timestamp":1769021202506,"version":"3.49.0"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100018919","name":"Major Key Project of Peng Cheng Laboratory","doi-asserted-by":"publisher","award":["PCL2023AS1-5"],"award-info":[{"award-number":["PCL2023AS1-5"]}],"id":[{"id":"10.13039\/100018919","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB1806800"],"award-info":[{"award-number":["2020YFB1806800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Province Basic and Applied Basic Research Foundation","award":["2019B1515120084"],"award-info":[{"award-number":["2019B1515120084"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,1,15]]},"DOI":"10.1109\/jiot.2024.3467275","type":"journal-article","created":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T19:29:33Z","timestamp":1727292573000},"page":"1760-1773","source":"Crossref","is-referenced-by-count":2,"title":["Rank-Two Correction and Fine-Tuning for Adaptive Byzantine Recovery in Federated Learning"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6831-9056","authenticated-orcid":false,"given":"Xinghan","family":"Wang","sequence":"first","affiliation":[{"name":"School of Cyber Science and Engineering, Southeast University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7406-2170","authenticated-orcid":false,"given":"Tingting","family":"Yang","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3368754"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3341811"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3041404"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2023.3242704"},{"key":"ref5","first-page":"1623","article-title":"Local model poisoning attacks to Byzantine-robust federated learning","volume-title":"Proc. 29th USENIX Secur. Symp.","author":"Fang"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom56396.2022.00030"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2022.3167434"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24498"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3314748"},{"key":"ref10","first-page":"1","article-title":"A little is enough: Circumventing defenses for distributed learning","volume-title":"Proc. 33rd Conf. Neural Inf. Process. Syst.","author":"Baruch"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3315226"},{"key":"ref12","first-page":"119","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. 31st Adv. Neural Inf. Process. Syst.","author":"Blanchard"},{"key":"ref13","first-page":"5636","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Yin"},{"key":"ref14","article-title":"Learning to detect malicious clients for robust federated learning","author":"Li","year":"2020","journal-title":"arXiv:2002.00211"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3145837"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3378329"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3321594"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/SP46215.2023.10179336"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IWQOS52092.2021.9521274"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2307\/2006193"},{"key":"ref21","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2022.3202887"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3351371"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3325634"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3153135"},{"key":"ref26","first-page":"634","article-title":"Analyzing federated learning through an adversarial lens","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Bhagoji"},{"key":"ref27","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017","journal-title":"arXiv:1708.07747"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref29","volume-title":"Learning Multiple Layers of Features from Tiny Images","author":"Krizhevsky","year":"2009"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2012.02.016"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/10836656\/10693508.pdf?arnumber=10693508","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T20:12:57Z","timestamp":1736971977000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10693508\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,15]]},"references-count":30,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3467275","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,15]]}}}