{"id":"https://openalex.org/W7131115721","doi":"https://doi.org/10.1109/tmc.2026.3665336","title":"A Model Consistency-Based Countermeasure to GAN-Based Data Poisoning Attack in Federated Learning","display_name":"A Model Consistency-Based Countermeasure to GAN-Based Data Poisoning Attack in Federated Learning","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131115721","doi":"https://doi.org/10.1109/tmc.2026.3665336"},"language":null,"primary_location":{"id":"doi:10.1109/tmc.2026.3665336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2026.3665336","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","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/A5102974942","display_name":"Wei Sun","orcid":"https://orcid.org/0000-0003-1015-1745"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Sun","raw_affiliation_strings":["Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2210-0152","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126600355","display_name":"Bo Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Gao","raw_affiliation_strings":["Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4377-2970","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126656895","display_name":"Ke Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Xiong","raw_affiliation_strings":["Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9364-0207","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Network Management Technology for High Speed Railway of Ministry of Education, School of Computer Science and Technology, Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101637865","display_name":"Yuwei Wang","orcid":"https://orcid.org/0000-0003-0931-2062"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwei Wang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3228-7371","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pingyi Fan","orcid":"https://orcid.org/0000-0002-0658-6079"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingyi Fan","raw_affiliation_strings":["Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0658-6079","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124122998","display_name":"Khaled Ben Letaief","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Khaled Ben Letaief","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0003-2519-6401","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I200769079","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18086275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"7","first_page":"10351","last_page":"10369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.4593999981880188,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.4593999981880188,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.44190001487731934,"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/T10237","display_name":"Cryptography and Data Security","score":0.008799999952316284,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.5547000169754028},{"id":"https://openalex.org/keywords/countermeasure","display_name":"Countermeasure","score":0.5109000205993652},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4860000014305115},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4287000000476837},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.38089999556541443},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.37940001487731934},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3686999976634979},{"id":"https://openalex.org/keywords/threat-model","display_name":"Threat model","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8389000296592712},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.7332000136375427},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5547000169754028},{"id":"https://openalex.org/C21593369","wikidata":"https://www.wikidata.org/wiki/Q1032176","display_name":"Countermeasure","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4860000014305115},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3686999976634979},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.3456000089645386},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.33550000190734863},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.32600000500679016},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C69360830","wikidata":"https://www.wikidata.org/wiki/Q1172237","display_name":"Data Protection Act 1998","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.2524999976158142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2026.3665336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2026.3665336","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.524394690990448,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G404331169","display_name":"\u9762\u5411\u4e34\u65f6\u70ed\u70b9\u7684\u65e0\u7ebf\u63a5\u5165\u7f51\u8d44\u6e90\u5206\u914d\u7406\u8bba\u4e0e\u6280\u672f\u7814\u7a76","funder_award_id":"61872028","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5269079536","display_name":null,"funder_award_id":"2024JBZY010","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8194416217","display_name":null,"funder_award_id":"2025JBXT010","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"federated":[1],"learning":[2],"(FL),":[3],"although":[4],"the":[5,144,223],"original":[6],"intention":[7],"of":[8,86,90,122,136,146,166,183,248],"\u201cavailable":[9],"but":[10,177],"not":[11,73],"visible\u201d":[12,33],"data":[13,17,38,139,156],"is":[14,115,238],"to":[15,53,83,173,192,240],"allay":[16],"privacy":[18],"concerns,":[19],"it":[20],"potentially":[21,100],"brings":[22],"new":[23,154],"security":[24],"threats,":[25],"particularly":[26,251],"poisoning":[27,39,140,157],"attacks":[28,40,197],"that":[29,217],"target":[30],"such":[31,37],"\u201cnot":[32],"local":[34,88,124],"data.":[35,94,180],"Intuitively,":[36],"have":[41,72],"great":[42],"potential":[43],"in":[44,77,103,244],"stealthily":[45],"degrading":[46],"global":[47],"FL":[48],"outcomes,":[49],"and":[50,80,162,214,228],"are":[51],"expected":[52],"be":[54,84,170,241],"even":[55],"stealthier":[56,101,149,195,252],"if":[57],"being":[58],"enhanced":[59],"by":[60,187],"generative":[61,64],"models":[62,125],"like":[63],"adversarial":[65],"networks":[66],"(GANs).":[67],"However,":[68],"existing":[69],"defense":[70,108,236],"methods":[71],"been":[74],"thoroughly":[75],"challenged":[76],"this":[78,104],"regard":[79],"generally":[81],"fail":[82],"aware":[85],"a":[87,96,106,119,153,246],"generation":[89],"seemingly":[91,175],"legitimate":[92,176],"poisoned":[93,179,249],"With":[95],"growing":[97],"concern":[98],"on":[99,206],"attacks,":[102,150],"paper,":[105],"cost-effective":[107],"mechanism":[109,237],"named":[110,160],"Model":[111],"Consistency-Based":[112],"Defense":[113],"(MCD)":[114],"proposed,":[116],"which":[117,168],"offers":[118],"comprehensive":[120],"examination":[121],"available":[123],"across":[126],"multiple":[127,207],"feature":[128],"dimensions,":[129],"providing":[130],"an":[131,163],"indirect":[132],"yet":[133],"effective":[134],"means":[135],"identifying":[137,245],"hidden":[138],"attackers.":[141],"To":[142],"push":[143],"limit":[145],"MCD":[147,191],"against":[148,194],"we":[151],"propose":[152],"GAN-based":[155,196],"attack":[158,219,226],"model":[159],"VagueGAN":[161,188],"unsupervised":[164],"variant":[165],"it,":[167],"can":[169],"flexibly":[171],"deployed":[172],"generate":[174],"noisy":[178],"The":[181],"consistency":[182],"GAN":[184],"outputs":[185],"revealed":[186],"helps":[189],"strengthen":[190],"work":[193],"as":[198,200],"well":[199],"other":[201],"mainstream":[202],"ones.":[203,254],"Extensive":[204],"experiments":[205],"open":[208],"datasets":[209],"(MNIST,":[210],"Fashion-MNIST,":[211],"CIFAR-10,":[212],"CIFAR-100,":[213],"Mini-Imagenet)":[215],"indicate":[216],"our":[218,235],"method":[220],"better":[221],"balances":[222],"trade-off":[224],"between":[225],"effectiveness":[227],"stealthiness":[229],"with":[230],"low":[231],"complexity.":[232],"More":[233],"importantly,":[234],"shown":[239],"more":[242],"competent":[243],"variety":[247],"data,":[250],"GAN-poisoned":[253]},"counts_by_year":[],"updated_date":"2026-06-06T06:22:57.294733","created_date":"2026-02-24T00:00:00"}
