{"id":"https://openalex.org/W4415883119","doi":"https://doi.org/10.1109/access.2025.3629353","title":"Fed-StackFPAD: Federated Learning for Face Presentation Attack Detection With Stacking to Tackle Data Heterogeneity","display_name":"Fed-StackFPAD: Federated Learning for Face Presentation Attack Detection With Stacking to Tackle Data Heterogeneity","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415883119","doi":"https://doi.org/10.1109/access.2025.3629353"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3629353","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3629353","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3629353","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057193506","display_name":"Mehmet Fatih G\u00fcndo\u011far","orcid":"https://orcid.org/0000-0002-6354-5281"},"institutions":[{"id":"https://openalex.org/I4210141776","display_name":"China XD Group (China)","ror":"https://ror.org/04ceqst84","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210141776"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mehmet Fatih G\u00fcndo\u011far","raw_affiliation_strings":["Department of Computer Engineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye"],"raw_orcid":"https://orcid.org/0000-0002-6354-5281","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye","institution_ids":["https://openalex.org/I4210141776"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041929046","display_name":"\u00c7i\u011fdem Ero\u011flu Erdem","orcid":"https://orcid.org/0000-0002-9264-5652"},"institutions":[{"id":"https://openalex.org/I1290270558","display_name":"Goodyear (United Kingdom)","ror":"https://ror.org/03tvt3c62","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290270558","https://openalex.org/I4210143271"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"\u00c7i\u011fdem Ero\u011flu Erdem","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Özyeğin University, İstanbul, Türkiye"],"raw_orcid":"https://orcid.org/0000-0002-9264-5652","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Özyeğin University, İstanbul, Türkiye","institution_ids":["https://openalex.org/I1290270558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050065869","display_name":"\u00d6mer Kor\u00e7ak","orcid":"https://orcid.org/0000-0003-4419-556X"},"institutions":[{"id":"https://openalex.org/I4210141776","display_name":"China XD Group (China)","ror":"https://ror.org/04ceqst84","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210141776"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"\u00d6mer Kor\u00e7ak","raw_affiliation_strings":["Department of Computer Engineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye"],"raw_orcid":"https://orcid.org/0000-0003-4419-556X","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Faculty of Engineering, Marmara University, İstanbul, Türkiye","institution_ids":["https://openalex.org/I4210141776"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9349,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80655353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"190354","last_page":"190370"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.7003999948501587,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11448","display_name":"Face recognition and analysis","score":0.7003999948501587,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10828","display_name":"Biometric Identification and Security","score":0.22390000522136688,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.013299999758601189,"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/robustness","display_name":"Robustness (evolution)","score":0.7084000110626221},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5663999915122986},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5566999912261963},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5199999809265137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.484499990940094},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4447000026702881},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44440001249313354},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.43209999799728394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9031999707221985},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7084000110626221},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5663999915122986},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5566999912261963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5322999954223633},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5199999809265137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.498199999332428},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4447000026702881},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44440001249313354},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4359000027179718},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4025000035762787},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.27970001101493835},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.25220000743865967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2025.3629353","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3629353","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c39c7a61d4cf4142bfbb82f27e12b944","is_oa":true,"landing_page_url":"https://doaj.org/article/c39c7a61d4cf4142bfbb82f27e12b944","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 190354-190370 (2025)","raw_type":"article"},{"id":"pmh:oai:eresearch.ozyegin.edu.tr:10679/11252","is_oa":true,"landing_page_url":"https://doi.org/10.1109/ACCESS.2025.3629353","pdf_url":null,"source":{"id":"https://openalex.org/S4306400232","display_name":"ECS Journal of Solid State Science and Technology (The Electrochemical Society)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2802273670","host_organization_name":"Electrochemical Society","host_organization_lineage":["https://openalex.org/I2802273670"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3629353","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3629353","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2930055764","display_name":null,"funder_award_id":"EEAG-122E025","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"},{"id":"https://openalex.org/G8842277822","display_name":null,"funder_award_id":"ARDEB-124E292","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"}],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Face":[0],"presentation":[1,31,108],"attack":[2,32,109],"detection":[3,110],"(FPAD)":[4],"is":[5,78],"crucial":[6],"for":[7,106],"ensuring":[8],"the":[9,23,28,61,130,143,150,158,200,210,221,227],"accuracy":[10],"and":[11,16,87,153,190,224],"reliability":[12],"of":[13,30,63,90,149],"face":[14,107],"recognition":[15],"verification":[17],"systems.":[18],"However,":[19,75],"existing":[20,170],"datasets":[21,165],"in":[22,27,142,157,176],"literature":[24],"exhibit":[25],"limitations":[26],"diversity":[29,70],"types":[33],"they":[34],"encompass.":[35],"Deep":[36],"learning-based":[37],"solutions":[38],"that":[39,111,167],"perform":[40],"well":[41,48],"on":[42,230],"one":[43],"dataset":[44,69],"may":[45],"not":[46],"generalize":[47],"to":[49,52,59],"others":[50],"due":[51],"domain":[53,178],"shift":[54],"issues.":[55],"A":[56],"potential":[57],"approach":[58],"improve":[60],"robustness":[62],"deep":[64],"learning":[65,103],"models":[66,156,223],"involves":[67],"expanding":[68],"through":[71,181],"multi-source":[72],"data":[73,85,92,138,154],"collection.":[74,93],"this":[76],"process":[77],"hindered":[79],"by":[80,207],"challenges":[81,180],"such":[82],"as":[83],"extensive":[84],"labeling":[86],"privacy":[88],"concerns":[89],"centralized":[91,137],"To":[94,215],"overcome":[95],"these":[96],"challenges,":[97],"we":[98,218],"introduce":[99],"Fed-StackFPAD,":[100],"a":[101,113,196],"federated":[102,151],"(FL)":[104],"framework":[105,132],"integrates":[112],"pretrained":[114],"self-supervised":[115,183],"transformer-based":[116],"masked":[117,184],"autoencoder":[118],"with":[119],"stacking-based":[120,191],"ensemble":[121],"learning.":[122],"By":[123],"leveraging":[124],"model":[125,152,192],"aggregation":[126],"across":[127],"multiple":[128],"clients,":[129],"proposed":[131],"enhances":[133],"performance":[134],"without":[135],"requiring":[136],"sharing.":[139],"The":[140],"meta-model":[141],"stacking":[144],"phase":[145],"combines":[146],"complementary":[147],"strengths":[148],"center-specific":[155],"ensemble.":[159],"Experimental":[160],"evaluations":[161],"using":[162,187],"4":[163],"different":[164],"demonstrate":[166],"Fed-StackFPAD":[168,194],"outperforms":[169],"state-of-the-art":[171],"methods,":[172],"highlighting":[173],"its":[174],"effectiveness":[175],"addressing":[177],"adaptation":[179],"FL,":[182],"image":[185],"modeling":[186],"vision":[188],"transformers,":[189],"aggregation.":[193],"demonstrates":[195],"significant":[197],"improvement,":[198],"lowering":[199],"average":[201],"half":[202],"total":[203],"error":[204],"rate":[205],"(HTER)":[206],"13.7%":[208],"over":[209],"current":[211],"best":[212],"FL":[213],"methods.":[214],"ensure":[216],"reproducibility,":[217],"publicly":[219],"share":[220],"fine-tuned":[222],"will":[225],"make":[226],"code":[228],"available":[229],"https://www.github.com/mehmetfatihgundogar/Fed-StackFPAD.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-04T00:00:00"}