{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T12:25:29Z","timestamp":1768393529245,"version":"3.49.0"},"reference-count":25,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100004787","name":"6G Flagship funded by the Research Council of Finland","doi-asserted-by":"publisher","award":["369116"],"award-info":[{"award-number":["369116"]}],"id":[{"id":"10.13039\/501100004787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100014438","name":"Emerging Projects Program, Infotech Oulu","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014438","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018948","name":"Business Finland through the Neural Pub\/Sub Co-Research Project","doi-asserted-by":"publisher","award":["8754\/31\/2022"],"award-info":[{"award-number":["8754\/31\/2022"]}],"id":[{"id":"10.13039\/501100018948","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Open J. Commun. Soc."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/ojcoms.2025.3646134","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T18:35:53Z","timestamp":1766082953000},"page":"370-385","source":"Crossref","is-referenced-by-count":0,"title":["Hybrid Reputation Aggregation: A Robust Defense Mechanism for Adversarial Federated Learning in 5G and Edge Network Environments"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3600-966X","authenticated-orcid":false,"given":"Saeid","family":"Sheikhi","sequence":"first","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, Oulu, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8545-599X","authenticated-orcid":false,"given":"Panos","family":"Kostakos","sequence":"additional","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, Oulu, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9475-4839","authenticated-orcid":false,"given":"Lauri","family":"Loven","sequence":"additional","affiliation":[{"name":"Center for Ubiquitous Computing, University of Oulu, Oulu, Finland"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2967670"},{"key":"ref2","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/EuCNC\/6GSummit58263.2023.10188245"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3333555"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-024-02285-2"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539231"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2024.3449563"},{"key":"ref8","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Bagdasaryan"},{"key":"ref9","first-page":"118","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Blanchard"},{"key":"ref10","article-title":"Mitigating sybils in federated learning poisoning","author":"Fung","year":"2018","journal-title":"arXiv:1808.04866"},{"key":"ref11","article-title":"The hidden vulnerability of distributed learning in byzantium","author":"Mhamdi","year":"2018","journal-title":"arXiv:1802.07927"},{"key":"ref12","first-page":"5650","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yin"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3153135"},{"key":"ref14","first-page":"634","article-title":"Analyzing federated learning through an adversarial lens","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Bhagoji"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/WACV61041.2025.00154"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CNS59707.2023.10288938"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-025-02753-3"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-023-04145-0"},{"key":"ref19","first-page":"1605","article-title":"Local model poisoning attacks to Byzantine-robust federated learning","volume-title":"Proc. 29th USENIX Security Symp.","author":"Fang"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24434"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3488932.3517395"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-91235-1_35"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3332512"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2023615"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72802-1_9"}],"container-title":["IEEE Open Journal of the Communications Society"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8782661\/11343983\/11303576.pdf?arnumber=11303576","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T07:14:18Z","timestamp":1768374858000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11303576\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/ojcoms.2025.3646134","relation":{},"ISSN":["2644-125X"],"issn-type":[{"value":"2644-125X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}