{"id":"https://openalex.org/W4415539532","doi":"https://doi.org/10.1145/3746027.3755595","title":"SiFMimicEvader: Evading Fake Voice Detection with Adversarial Neural Mimicry Attacks","display_name":"SiFMimicEvader: Evading Fake Voice Detection with Adversarial Neural Mimicry Attacks","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539532","doi":"https://doi.org/10.1145/3746027.3755595"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075219529","display_name":"Xuan Hai","orcid":"https://orcid.org/0009-0002-0695-2187"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Hai","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-0695-2187","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352330","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0003-3685-4852"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3685-4852","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012640517","display_name":"Zihao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihao Zhang","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-5737-1301","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030392751","display_name":"Ziyao Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyao Yu","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-8312-1881","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100978844","display_name":"Xiangzhen Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangzhen Kong","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-4829-3126","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448208","display_name":"Song Li","orcid":"https://orcid.org/0000-0002-7961-8502"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Li","raw_affiliation_strings":["The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China and Hangzhou High-Tech Zone (Bin jiang) Institute of Blockchain and Data Security, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7961-8502","affiliations":[{"raw_affiliation_string":"The State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China and Hangzhou High-Tech Zone (Bin jiang) Institute of Blockchain and Data Security, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029715489","display_name":"Weina Niu","orcid":"https://orcid.org/0000-0002-3235-3463"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weina Niu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-3235-3463","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114549552","display_name":"Rui Zhou","orcid":"https://orcid.org/0000-0002-9968-6190"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhou","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9968-6190","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100604365","display_name":"Qingguo Zhou","orcid":"https://orcid.org/0000-0001-8054-5446"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingguo Zhou","raw_affiliation_strings":["Lanzhou University, Lanzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-8054-5446","affiliations":[{"raw_affiliation_string":"Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11619","last_page":"11628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9990000128746033,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9990000128746033,"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":0.9861000180244446,"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/T10860","display_name":"Speech and Audio Processing","score":0.974399983882904,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mimicry","display_name":"Mimicry","score":0.8047000169754028},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7784000039100647},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5730999708175659},{"id":"https://openalex.org/keywords/cloning","display_name":"Cloning (programming)","score":0.487199991941452},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45500001311302185},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42089998722076416},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.41350001096725464}],"concepts":[{"id":"https://openalex.org/C7863114","wikidata":"https://www.wikidata.org/wiki/Q192627","display_name":"Mimicry","level":2,"score":0.8047000169754028},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039000034332275},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7784000039100647},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5730999708175659},{"id":"https://openalex.org/C121050878","wikidata":"https://www.wikidata.org/wiki/Q5135020","display_name":"Cloning (programming)","level":2,"score":0.487199991941452},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4713999927043915},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42089998722076416},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.41350001096725464},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.37400001287460327},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.36579999327659607},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3626999855041504},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35749998688697815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3057999908924103},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2870999872684479},{"id":"https://openalex.org/C11560541","wikidata":"https://www.wikidata.org/wiki/Q1756025","display_name":"Replay attack","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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":12,"referenced_works":["https://openalex.org/W2962747881","https://openalex.org/W2964243274","https://openalex.org/W3093077017","https://openalex.org/W3110588169","https://openalex.org/W3161011913","https://openalex.org/W3163596559","https://openalex.org/W3170179936","https://openalex.org/W3174037065","https://openalex.org/W4310295314","https://openalex.org/W4385975857","https://openalex.org/W4403791925","https://openalex.org/W6960281296"],"related_works":[],"abstract_inverted_index":{"The":[0,117],"application":[1],"of":[2,13,76,130,138,153],"deep":[3],"learning":[4],"in":[5,176,186],"voice":[6,18,107,132],"cloning":[7,19],"has":[8],"significantly":[9,166],"enhanced":[10],"the":[11,55,74,124,128,151],"quality":[12,178],"cloned":[14],"voices.":[15],"While":[16],"advanced":[17],"technologies":[20],"are":[21],"widely":[22],"applied":[23],"across":[24,163],"various":[25,164],"domains,":[26],"they":[27],"also":[28,172],"pose":[29],"serious":[30],"security":[31],"challenges":[32],"such":[33],"as":[34,123,142],"producing":[35],"natural":[36],"Deepfakes.":[37],"In":[38],"response,":[39],"numerous":[40],"studies":[41],"have":[42],"focused":[43],"on":[44,88],"detecting":[45],"fake":[46,106,131],"voices,":[47],"with":[48,109],"many":[49],"reporting":[50],"outstanding":[51],"performance.":[52],"However,":[53],"is":[54],"issue":[56],"truly":[57],"resolved?":[58],"This":[59],"paper":[60],"introduces":[61],"Adversarial":[62],"Neural":[63],"Mimicry":[64],"Attack":[65],"(ANMA)":[66],"which":[67],"leverages":[68],"a":[69,96,136],"specialized":[70],"model":[71],"to":[72,104,126,144],"predict":[73,127],"behavior":[75],"other":[77,168],"similar":[78],"models,":[79],"transforming":[80],"black-box":[81,98],"attacks":[82],"into":[83],"white-box":[84],"scenarios":[85],"indirectly.":[86],"Based":[87],"ANMA":[89],"and":[90,113,134,179],"Speaker-irrelative":[91],"Features":[92],"(SiFs),":[93],"we":[94],"propose":[95],"novel":[97],"attack":[99,158,169],"framework":[100,118],"called":[101],"SiFMimicEvader,":[102,154],"designed":[103],"evade":[105],"detectors":[108,133],"high":[110,184],"success":[111,159],"rates":[112],"minimal":[114],"query":[115,180],"requirements.":[116],"utilizes":[119],"speech":[120],"representation":[121],"models":[122],"breakthrough":[125],"behaviors":[129],"employs":[135],"series":[137],"SiFs":[139],"editing":[140],"operations":[141],"perturbations":[143],"deceive":[145],"these":[146],"detectors.":[147],"Experimental":[148],"results":[149],"demonstrate":[150],"effectiveness":[152],"achieving":[155],"an":[156],"average":[157],"rate":[160],"exceeding":[161],"50%":[162],"detectors,":[165],"outperforming":[167],"methods,":[170],"while":[171],"showing":[173],"great":[174],"performance":[175],"audio":[177],"scale,":[181],"indicating":[182],"its":[183],"availability":[185],"real-world":[187],"scenarios.":[188]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}