{"id":"https://openalex.org/W7138087535","doi":"https://doi.org/10.1109/access.2026.3674500","title":"Multi-Layer Knowledge Distillation With Custom Temperature Scaling for Deepfake Detection","display_name":"Multi-Layer Knowledge Distillation With Custom Temperature Scaling for Deepfake Detection","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7138087535","doi":"https://doi.org/10.1109/access.2026.3674500"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3674500","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674500","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.2026.3674500","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129686629","display_name":"Eva Hemantkumar Shah","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Eva Hemantkumar Shah","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120718626","display_name":"Utkarsh Dubey","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Utkarsh Dubey","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129686612","display_name":"Arshaq Shagihan Abdul Rahiman","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arshaq Shagihan Abdul Rahiman","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004645143","display_name":"Nisha P. Shetty","orcid":"https://orcid.org/0000-0002-4738-4713"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nisha P. Shetty","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India"],"raw_orcid":"https://orcid.org/0000-0002-4738-4713","affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129686629"],"corresponding_institution_ids":["https://openalex.org/I164861460"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48791978,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"46763","last_page":"46787"},"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":0.6931999921798706,"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":0.6931999921798706,"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":0.03060000017285347,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.021400000900030136,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.6442999839782715},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5045999884605408},{"id":"https://openalex.org/keywords/temperature-measurement","display_name":"Temperature measurement","score":0.2937999963760376},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.28929999470710754},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.2888999879360199}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7045999765396118},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.6442999839782715},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5045999884605408},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.3747999966144562},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33719998598098755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3301999866962433},{"id":"https://openalex.org/C72293138","wikidata":"https://www.wikidata.org/wiki/Q909741","display_name":"Temperature measurement","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.26910001039505005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3674500","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674500","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:ad04b3fb2bef46d0ab30542fafd418f5","is_oa":true,"landing_page_url":"https://doaj.org/article/ad04b3fb2bef46d0ab30542fafd418f5","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 14, Pp 46763-46787 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3674500","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3674500","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":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.506788969039917}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,36],"swift":[1],"emergence":[2],"of":[3,40,47,88,211,216,235],"highly":[4],"convincing":[5],"deepfakes":[6],"on":[7,54],"social":[8,34],"media":[9],"and":[10,21,33,68,82,114,159,176,197,213,273],"digital":[11,18],"platforms":[12,272],"has":[13],"posed":[14],"considerable":[15],"difficulties":[16],"to":[17,78,117,136,155,170,262],"security,":[19],"privacy,":[20],"public":[22],"confidence,":[23],"as":[24],"these":[25,60],"fabrications":[26],"are":[27,62,85,128],"increasingly":[28],"used":[29,242],"for":[30,131,243,253],"financial":[31],"deception":[32],"manipulation.":[35],"enormous":[37],"computational":[38],"demands":[39],"high-capacity":[41,72,164],"models":[42,123],"now":[43],"impede":[44],"the":[45,55,168,172,201,220,227,244],"deployment":[46,255],"effective":[48],"defense":[49],"measures,":[50],"preventing":[51],"real-time":[52,265],"authentication":[53],"resource-constrained":[56],"edge":[57],"devices":[58],"where":[59],"forgeries":[61],"most":[63,245],"frequently":[64,104],"encountered.":[65],"Deep":[66],"learning":[67],"machine":[69],"learning,":[70],"particularly":[71],"convolutional":[73],"neural":[74],"networks":[75],"(CNNs)":[76],"intended":[77],"examine":[79],"temporal":[80],"irregularities":[81],"facial":[83],"textures,":[84],"key":[86],"components":[87],"current":[89,93],"detection":[90,112,267],"methods.":[91],"These":[92,223],"approaches,":[94],"however,":[95],"have":[96],"a":[97,107,115,143,151,163,187,208,232,259],"crucial":[98,182],"trade-off:":[99],"while":[100,180],"naive":[101],"model":[102,206],"compression":[103],"results":[105],"in":[106,110],"significant":[108],"loss":[109],"forensic":[111,183],"performance":[113],"failure":[116],"retain":[118],"fine-grained":[119],"feature":[120],"representations,":[121],"larger":[122],"achieve":[124],"high":[125,233],"accuracy":[126,210,234],"but":[127],"too":[129],"slow":[130],"mobile":[132],"deployment.":[133],"In":[134],"order":[135],"close":[137],"this":[138],"gap,":[139],"our":[140],"study":[141],"develops":[142],"multi-layer":[144],"Knowledge":[145],"Distillation":[146],"(KD)":[147],"system":[148],"that":[149,226],"allows":[150],"lightweight":[152],"student,":[153],"EfficientNet-B0,":[154],"receive":[156],"decision-level,":[157],"feature-level,":[158],"attention-level":[160],"knowledge":[161],"from":[162],"Xception":[165],"teacher.We":[166],"allow":[167],"learner":[169],"imitate":[171],"teacher\u2019s":[173,221],"internal":[174],"representations":[175],"spatial":[177],"focus":[178],"areas":[179],"maintaining":[181],"clues":[184],"by":[185],"using":[186],"bespoke":[188],"\"gentle\"":[189],"temperature":[190],"scaling":[191],"schedule.":[192],"With":[193],"4x":[194],"fewer":[195,199],"parameters":[196],"20x":[198],"processes,":[200],"suggested":[202],"Student":[203],"Temp":[204],"2":[205],"obtained":[207],"remarkable":[209],"97.23%":[212],"an":[214],"AUC":[215],"0.9942,":[217],"somewhat":[218],"surpassing":[219],"accuracy.":[222],"findings":[224],"suggest":[225],"ShuffleNetV2-KD":[228],"variation,":[229],"which":[230],"maintains":[231],"95.45%":[236],"with":[237],"only":[238],"1.25M":[239],"parameters,":[240],"be":[241],"severe":[246],"resource":[247],"limitations.":[248],"This":[249],"framework":[250],"is":[251],"essential":[252],"practical":[254],"since":[256],"it":[257],"offers":[258],"scalable":[260],"way":[261],"include":[263],"reliable,":[264],"deepfake":[266],"straight":[268],"into":[269],"edge-based":[270],"communication":[271],"smartphones.":[274]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-03-18T00:00:00"}
