{"id":"https://openalex.org/W7131076131","doi":"https://doi.org/10.1109/iccvw69036.2025.00161","title":"SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection Against Adversarial Attacks","display_name":"SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection Against Adversarial Attacks","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131076131","doi":"https://doi.org/10.1109/iccvw69036.2025.00161"},"language":null,"primary_location":{"id":"doi:10.1109/iccvw69036.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-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/A5126637352","display_name":"Kutub Uddin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092198","display_name":"University of Michigan\u2013Flint","ror":"https://ror.org/01c3xc117","country_code":"US","type":"education","lineage":["https://openalex.org/I4210092198"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kutub Uddin","raw_affiliation_strings":["College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502","institution_ids":["https://openalex.org/I4210092198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101518388","display_name":"Awais Khan","orcid":"https://orcid.org/0009-0009-5919-1538"},"institutions":[{"id":"https://openalex.org/I4210092198","display_name":"University of Michigan\u2013Flint","ror":"https://ror.org/01c3xc117","country_code":"US","type":"education","lineage":["https://openalex.org/I4210092198"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Awais Khan","raw_affiliation_strings":["College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502","institution_ids":["https://openalex.org/I4210092198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126648589","display_name":"Muhammad Umar Farooq","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092198","display_name":"University of Michigan\u2013Flint","ror":"https://ror.org/01c3xc117","country_code":"US","type":"education","lineage":["https://openalex.org/I4210092198"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Umar Farooq","raw_affiliation_strings":["College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502","institution_ids":["https://openalex.org/I4210092198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024102795","display_name":"Khalid Mahmood Malik","orcid":"https://orcid.org/0000-0002-7927-3436"},"institutions":[{"id":"https://openalex.org/I4210092198","display_name":"University of Michigan\u2013Flint","ror":"https://ror.org/01c3xc117","country_code":"US","type":"education","lineage":["https://openalex.org/I4210092198"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khalid Mahmood Malik","raw_affiliation_strings":["College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Innovation & Technology, University of Michigan-Flint,MI,USA,48502","institution_ids":["https://openalex.org/I4210092198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.81858355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1513","last_page":"1522"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9466000199317932,"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":0.9466000199317932,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.020099999383091927,"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":0.004000000189989805,"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/generative-grammar","display_name":"Generative grammar","score":0.8615999817848206},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6581000089645386},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5612999796867371},{"id":"https://openalex.org/keywords/generative-design","display_name":"Generative Design","score":0.5435000061988831},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.4431000053882599},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.4074000120162964}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.8615999817848206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7461000084877014},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6581000089645386},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5612999796867371},{"id":"https://openalex.org/C184408114","wikidata":"https://www.wikidata.org/wiki/Q1502022","display_name":"Generative Design","level":3,"score":0.5435000061988831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138000249862671},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.4074000120162964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38589999079704285},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3100000023841858},{"id":"https://openalex.org/C138081364","wikidata":"https://www.wikidata.org/wiki/Q852013","display_name":"Shield","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27970001101493835}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00161","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-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/W2936802426","https://openalex.org/W2963341071","https://openalex.org/W2963775347","https://openalex.org/W3016138785","https://openalex.org/W3081360282","https://openalex.org/W3137367938","https://openalex.org/W3163596559","https://openalex.org/W3170179936","https://openalex.org/W3196774886","https://openalex.org/W3211424380","https://openalex.org/W4223915588","https://openalex.org/W4226492220","https://openalex.org/W4297841773","https://openalex.org/W4297841787","https://openalex.org/W4379046716","https://openalex.org/W4382371735","https://openalex.org/W4383215383","https://openalex.org/W4385823506","https://openalex.org/W4389474419","https://openalex.org/W4390097598","https://openalex.org/W4390523451","https://openalex.org/W4392902701","https://openalex.org/W4392910532","https://openalex.org/W4394617057","https://openalex.org/W4402916306","https://openalex.org/W4403791925","https://openalex.org/W4405182531","https://openalex.org/W4408352962","https://openalex.org/W4409917641","https://openalex.org/W4412836818"],"related_works":[],"abstract_inverted_index":{"Audio":[0],"plays":[1],"a":[2,61,102],"crucial":[3],"role":[4],"in":[5,193,201],"applications":[6],"like":[7],"speaker":[8],"verification,":[9],"voice-enabled":[10],"smart":[11],"devices,":[12],"and":[13,97,110,116,133,162,183,191,196,199,208],"audio":[14,17,41],"conferencing.":[15],"However,":[16],"manipulations,":[18],"such":[19],"as":[20],"deepfakes,":[21],"pose":[22],"significant":[23],"risks":[24],"by":[25,94],"enabling":[26],"the":[27,85,127,146,205],"spread":[28],"of":[29,188],"misinformation.":[30],"Our":[31],"empirical":[32],"analysis":[33],"reveals":[34],"that":[35],"existing":[36],"methods":[37],"for":[38,108,154,160,167,169,204],"detecting":[39],"deepfake":[40],"are":[42],"often":[43],"vulnerable":[44],"to":[45,68,105,152,158,165],"anti-forensic":[46],"(AF)":[47],"attacks,":[48],"particularly":[49],"those":[50],"attacked":[51,112],"using":[52,119],"generative":[53,71,82,88,121,130,139,172],"adversarial":[54],"networks.":[55],"In":[56],"this":[57],"article,":[58],"we":[59,78,100],"propose":[60],"novel":[62],"integrated":[63,92],"learning":[64,93],"method":[65],"called":[66,84],"SHIELD":[67,125,176],"defend":[69],"against":[70,129,180],"AF":[72,76,111,131,143,181],"attacks.":[73],"To":[74],"expose":[75],"signatures,":[77],"integrate":[79],"an":[80,185],"auxiliary":[81,120],"model,":[83,89],"defense":[86,128],"(DF)":[87],"which":[90],"facilitates":[91],"combining":[95],"input":[96],"output.":[98],"Furthermore,":[99],"design":[101],"triplet":[103],"model":[104],"capture":[106],"correlations":[107],"real":[109],"audios":[113,118],"with":[114],"real-generated":[115],"attacked-generated":[117],"models.":[122,140,173],"The":[123,141,174],"proposed":[124,142,175],"strengthens":[126],"attacks":[132,182],"achieves":[134,184],"robust":[135,179],"performance":[136],"across":[137],"various":[138],"significantly":[144],"reduces":[145],"average":[147,186],"detection":[148],"accuracy":[149,187],"from":[150,156,163],"95.49%":[151],"59.77%":[153],"ASVspoof2019,":[155,206],"99.44%":[157],"38.45%":[159],"In-the-Wild,":[161,207],"98.41%":[164],"51.18%":[166],"HalfTruth":[168,209],"three":[170],"different":[171],"mechanism":[177],"is":[178],"98.13%,":[189],"98.58%,":[190],"99.57%":[192],"match":[194],"setting":[195,203],"98.78%,":[197],"98.62%,":[198],"98.85%":[200],"mismatch":[202],"datasets,":[210],"respectively.":[211]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-24T00:00:00"}