{"id":"https://openalex.org/W4416366568","doi":"https://doi.org/10.1109/jiot.2025.3634793","title":"Robust Federated Learning With Heterogeneous Clients via Classifier Calibration and Alignment","display_name":"Robust Federated Learning With Heterogeneous Clients via Classifier Calibration and Alignment","publication_year":2025,"publication_date":"2025-11-19","ids":{"openalex":"https://openalex.org/W4416366568","doi":"https://doi.org/10.1109/jiot.2025.3634793"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2025.3634793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3634793","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102922010","display_name":"Yu Qiao","orcid":"https://orcid.org/0000-0003-4045-8473"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yu Qiao","raw_affiliation_strings":["School of Computing, Kyung Hee University, Yongin-si, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computing, Kyung Hee University, Yongin-si, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053171293","display_name":"Zilong Jin","orcid":"https://orcid.org/0000-0001-5608-7748"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zilong Jin","raw_affiliation_strings":["School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou, China","School of Information Science and Engineering, Zhejiang Sci-tech University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]},{"raw_affiliation_string":"School of Information Science and Engineering, Zhejiang Sci-tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046015188","display_name":"Avi Deb Raha","orcid":"https://orcid.org/0000-0003-0240-1214"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Avi Deb Raha","raw_affiliation_strings":["School of Computing, Kyung Hee University, Yongin-si, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computing, Kyung Hee University, Yongin-si, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021511574","display_name":"Apurba Adhikary","orcid":"https://orcid.org/0000-0003-3970-1878"},"institutions":[{"id":"https://openalex.org/I315729180","display_name":"Noakhali Science and Technology University","ror":"https://ror.org/05q9we431","country_code":"BD","type":"education","lineage":["https://openalex.org/I315729180"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Apurba Adhikary","raw_affiliation_strings":["Department of Information and Communication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Noakhali Science and Technology University, Noakhali, Bangladesh","institution_ids":["https://openalex.org/I315729180"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000263913","display_name":"Eui\u2010Nam Huh","orcid":"https://orcid.org/0000-0003-0184-6975"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eui-Nam Huh","raw_affiliation_strings":["School of Computing, Kyung Hee University, Yongin-si, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computing, Kyung Hee University, Yongin-si, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091266202","display_name":"Dusit Niyato","orcid":"https://orcid.org/0000-0002-7442-7416"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dusit Niyato","raw_affiliation_strings":["College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore","College of Computing and Data Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"College of Computing and Data Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063667378","display_name":"Zhu Han","orcid":null},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhu Han","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034052371","display_name":"Choong Seon Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Choong Seon Hong","raw_affiliation_strings":["School of Computing, Kyung Hee University, Yongin-si, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Computing, Kyung Hee University, Yongin-si, Republic of Korea","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5102922010"],"corresponding_institution_ids":["https://openalex.org/I35928602"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19784313,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"4","first_page":"5957","last_page":"5971"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.4754999876022339,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.4754999876022339,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.38440001010894775,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.021299999207258224,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.9086999893188477},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.8553000092506409},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7436000108718872},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4683000147342682},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46779999136924744},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.4399999976158142},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.3440000116825104},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3019999861717224}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.9086999893188477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8776999711990356},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.8553000092506409},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7436000108718872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.534500002861023},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4715999960899353},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.4399999976158142},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4178999960422516},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3418000042438507},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.2912999987602234},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3634793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3634793","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2746600820","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W3107235539","https://openalex.org/W3113075536","https://openalex.org/W4281486913","https://openalex.org/W4283796083","https://openalex.org/W4291972732","https://openalex.org/W4293846201","https://openalex.org/W4321488467","https://openalex.org/W4381734432","https://openalex.org/W4382237406","https://openalex.org/W4382318106","https://openalex.org/W4386076561","https://openalex.org/W4387105517","https://openalex.org/W4387146104","https://openalex.org/W4387249807","https://openalex.org/W4390018122","https://openalex.org/W4400355554","https://openalex.org/W4401508561","https://openalex.org/W4401665468","https://openalex.org/W4403826771","https://openalex.org/W4404787909","https://openalex.org/W4405175807","https://openalex.org/W4408361606","https://openalex.org/W4414265937","https://openalex.org/W4414788006","https://openalex.org/W4414941100","https://openalex.org/W4416228982"],"related_works":[],"abstract_inverted_index":{"Robust":[0],"Federated":[1],"Learning":[2],"(RoFL)":[3],"extends":[4],"traditional":[5],"federated":[6,179],"learning,":[7],"not":[8],"only":[9],"by":[10,29,60],"enabling":[11],"multiple":[12],"clients":[13],"to":[14,37,56,94,117,162,206],"collaboratively":[15],"train":[16],"a":[17,88,108,147,190,197],"shared":[18,142],"model":[19,75],"under":[20],"the":[21,57,119,168,171],"coordination":[22],"of":[23,121,170],"an":[24],"edge":[25],"server,":[26],"but":[27],"also":[28,53],"incorporating":[30,125],"client-side":[31],"defense":[32,211],"mechanisms":[33],"(e.g.,":[34],"adversarial":[35,40,101,151,160,201,213],"training)":[36],"defend":[38],"against":[39,100,212],"attacks":[41],"while":[42,98],"preserving":[43],"data":[44,66],"privacy.":[45],"However,":[46],"recent":[47],"studies":[48],"have":[49],"shown":[50],"that":[51,113],"RoFL":[52,90],"remains":[54],"vulnerable":[55],"challenges":[58,97],"posed":[59],"non-independent":[61],"and":[62,77,159,184,196,210],"identically":[63],"distributed":[64],"(non-IID)":[65],"distributions":[67],"across":[68,181],"heterogeneous":[69],"clients,":[70],"which":[71,154,174],"can":[72,132],"degrade":[73],"overall":[74],"generalization":[76,209],"robustness.":[78,164],"To":[79],"mitigate":[80,118],"this":[81,84],"challenge,":[82],"in":[83,193,200],"paper,":[85],"we":[86,105,145],"propose":[87,146],"novel":[89],"framework,":[91],"called":[92],"RoFLCCA,":[93,173],"address":[95],"non-IID":[96,122],"defending":[99],"attacks.":[102],"In":[103],"particular,":[104],"first":[106],"introduce":[107],"local":[109],"classifier":[110,135],"calibration":[111],"mechanism":[112],"utilizes":[114],"feature-level":[115],"augmentation":[116],"effects":[120],"data.":[123],"By":[124],"global":[126,150],"class-wise":[127],"feature":[128],"statistics,":[129],"each":[130],"client":[131],"adjust":[133],"its":[134,204],"using":[136],"synthetic":[137],"features":[138],"derived":[139],"from":[140],"these":[141],"representations.":[143],"Second,":[144],"calibrated":[148],"classifier-guided":[149],"alignment":[152],"strategy,":[153],"enforces":[155],"consistency":[156],"between":[157],"augmented":[158],"predictions":[161],"improve":[163],"Simulation":[165],"results":[166],"demonstrate":[167],"effectiveness":[169],"proposed":[172],"consistently":[175],"outperforms":[176],"existing":[177],"robust":[178],"baselines":[180],"different":[182],"datasets":[183],"settings.":[185],"On":[186],"average,":[187],"it":[188],"achieves":[189],"7.07%":[191],"improvement":[192],"clean":[194],"accuracy":[195],"4.71%":[198],"gain":[199],"robustness,":[202],"highlighting":[203],"ability":[205],"enhance":[207],"both":[208],"threats.":[214]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-19T00:00:00"}
