{"id":"https://openalex.org/W7127430175","doi":"https://doi.org/10.1109/access.2026.3660914","title":"TFD-Video: Threshold-Aware Federated Deepfake Detection for Video Forensics","display_name":"TFD-Video: Threshold-Aware Federated Deepfake Detection for Video Forensics","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7127430175","doi":"https://doi.org/10.1109/access.2026.3660914"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3660914","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660914","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.2026.3660914","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087874434","display_name":"Maryam Al-Fehani","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]},{"id":"https://openalex.org/I92528248","display_name":"Qatar Foundation","ror":"https://ror.org/01cawbq05","country_code":"QA","type":"funder","lineage":["https://openalex.org/I92528248"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Maryam Al-Fehani","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0002-2399-5712","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839","https://openalex.org/I92528248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124945188","display_name":"Abdullatif Al-Baseer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]},{"id":"https://openalex.org/I92528248","display_name":"Qatar Foundation","ror":"https://ror.org/01cawbq05","country_code":"QA","type":"funder","lineage":["https://openalex.org/I92528248"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Abdullatif Al-Baseer","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0002-6886-6500","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839","https://openalex.org/I92528248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124928460","display_name":"Saif Al-Kuwari","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]},{"id":"https://openalex.org/I92528248","display_name":"Qatar Foundation","ror":"https://ror.org/01cawbq05","country_code":"QA","type":"funder","lineage":["https://openalex.org/I92528248"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Saif Al-Kuwari","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0002-4402-7710","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839","https://openalex.org/I92528248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":15.486,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98405253,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"14","issue":null,"first_page":"23264","last_page":"23278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7175999879837036,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7175999879837036,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.06530000269412994,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.04659999907016754,"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/payload","display_name":"Payload (computing)","score":0.7835000157356262},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6241000294685364},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5996000170707703},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5504999756813049},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5156999826431274},{"id":"https://openalex.org/keywords/low-latency","display_name":"Low latency (capital markets)","score":0.4072999954223633},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.40709999203681946},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.38929998874664307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9068999886512756},{"id":"https://openalex.org/C134066672","wikidata":"https://www.wikidata.org/wiki/Q1424639","display_name":"Payload (computing)","level":3,"score":0.7835000157356262},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6241000294685364},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5996000170707703},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5504999756813049},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5156999826431274},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.41909998655319214},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38940000534057617},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38929998874664307},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3601999878883362},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C2988656282","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity detection","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C2983174267","wikidata":"https://www.wikidata.org/wiki/Q3775098","display_name":"Video retrieval","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2854999899864197},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C165136773","wikidata":"https://www.wikidata.org/wiki/Q1363179","display_name":"Single point of failure","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3660914","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660914","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"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3660914","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660914","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2606891064","https://openalex.org/W2909336075","https://openalex.org/W2963363373","https://openalex.org/W2982058372","https://openalex.org/W3034713808","https://openalex.org/W3158734383","https://openalex.org/W3166428200","https://openalex.org/W3183392865","https://openalex.org/W3195746634","https://openalex.org/W3196204467","https://openalex.org/W4200380909","https://openalex.org/W4214661097","https://openalex.org/W4281861252","https://openalex.org/W4290617287","https://openalex.org/W4310055000","https://openalex.org/W4312909749","https://openalex.org/W4313396675","https://openalex.org/W4313984387","https://openalex.org/W4316661129","https://openalex.org/W4320013936","https://openalex.org/W4379033874","https://openalex.org/W4381300935","https://openalex.org/W4381885798","https://openalex.org/W4383753813","https://openalex.org/W4386075957","https://openalex.org/W4391262065","https://openalex.org/W4393170546","https://openalex.org/W4394625735","https://openalex.org/W4400041386","https://openalex.org/W4403242972","https://openalex.org/W4403664746","https://openalex.org/W4403791710","https://openalex.org/W4405778546","https://openalex.org/W4407783194","https://openalex.org/W4415674181","https://openalex.org/W4415796518","https://openalex.org/W7114809294"],"related_works":[],"abstract_inverted_index":{"Deepfakes":[0],"and":[1,5,25,42,90,100,123,161,168,174,185],"other":[2],"AI-based":[3],"manipulated":[4],"synthesized":[6],"videos":[7],"pose":[8],"a":[9,66,79,115,146],"rising":[10],"threat,":[11],"yet":[12],"training":[13],"robust":[14],"detectors":[15],"under":[16],"federated":[17,44],"settings":[18],"is":[19,23,27],"challenging,":[20],"where":[21],"data":[22,124],"siloed":[24],"communication":[26,133],"limited.":[28],"Existing":[29],"compression":[30],"strategies":[31],"for":[32,40],"Federated":[33,62],"Learning":[34],"(FL)":[35],"can":[36,181],"reduce":[37,183],"detection":[38,164,190],"accuracy":[39],"forensics,":[41],"standard":[43],"averaging":[45],"(FedAvg)":[46],"may":[47],"weaken":[48],"client-specific":[49],"adaptations":[50],"that":[51,68,87,179],"are":[52],"important":[53],"in":[54],"practice.":[55],"To":[56],"this":[57],"end,":[58],"we":[59],"propose":[60],"Threshold-Aware":[61],"Deepfake":[63],"Detection":[64],"(TFD),":[65],"framework":[67],"combines":[69],"communication-efficient":[70],"structured":[71,92],"sparsification":[72],"with":[73,83],"client-side":[74],"optimization.":[75],"Each":[76],"client":[77,143],"augments":[78],"shared":[80],"video":[81,158],"backbone":[82],"learnable":[84],"per-filter":[85],"thresholds":[86,101],"gate":[88],"computations":[89],"induce":[91],"sparsity.":[93],"During":[94],"training,":[95],"clients":[96],"update":[97],"local":[98,151],"weights":[99],"but":[102],"transmit":[103],"only":[104],"compact":[105],"threshold":[106],"vectors.":[107],"The":[108,176],"server":[109],"aggregates":[110],"these":[111],"vectors":[112],"to":[113,144,149,193],"establish":[114],"common":[116],"sparsity":[117],"pattern,":[118],"while":[119,140,187],"dense":[120],"model":[121,147],"parameters":[122],"remain":[125],"local.":[126],"This":[127],"efficient":[128],"threshold-sharing":[129],"scheme":[130],"dramatically":[131],"reduces":[132],"overhead":[134],"by":[135],"several":[136],"orders":[137],"of":[138],"magnitude":[139],"enabling":[141],"each":[142],"maintain":[145],"tailored":[148],"its":[150],"data.":[152],"We":[153],"evaluate":[154],"TFD":[155,180],"on":[156],"deepfake":[157],"benchmarks":[159],"(FaceForensics++":[160],"Celeb-DF),":[162],"reporting":[163],"metrics":[165],"(accuracy,":[166],"AUROC/AUPRC)":[167],"efficiency":[169],"indicators":[170],"(per-round":[171],"payload":[172],"size":[173],"costs).":[175],"results":[177],"indicate":[178],"significantly":[182],"costs":[184],"latency":[186],"maintaining":[188],"competitive":[189],"performance":[191],"relative":[192],"state-of-the-art":[194],"approaches.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-02-04T00:00:00"}
