{"id":"https://openalex.org/W3162258435","doi":"https://doi.org/10.1109/icassp39728.2021.9413467","title":"Attack on Practical Speaker Verification System Using Universal Adversarial Perturbations","display_name":"Attack on Practical Speaker Verification System Using Universal Adversarial Perturbations","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3162258435","doi":"https://doi.org/10.1109/icassp39728.2021.9413467","mag":"3162258435"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2105.09022","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100718235","display_name":"Weiyi Zhang","orcid":"https://orcid.org/0000-0003-1296-3579"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyi Zhang","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050525860","display_name":"Shuning Zhao","orcid":"https://orcid.org/0000-0002-9137-386X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuning Zhao","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120543308","display_name":"Le Liu","orcid":"https://orcid.org/0000-0002-5478-1952"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Le Liu","raw_affiliation_strings":["Beijing d-Ear Technologies Co.,Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing d-Ear Technologies Co.,Ltd","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100372739","display_name":"Jianmin Li","orcid":"https://orcid.org/0000-0002-4937-2433"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianmin Li","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089344893","display_name":"Xingliang Cheng","orcid":"https://orcid.org/0000-0002-1955-3970"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingliang Cheng","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084318285","display_name":"Thomas Fang Zheng","orcid":"https://orcid.org/0000-0002-0249-4767"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Thomas Fang Zheng","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004579631","display_name":"Xiaolin Hu","orcid":"https://orcid.org/0000-0002-4907-7354"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Hu","raw_affiliation_strings":["Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2575","last_page":"2579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.996999979019165,"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":0.996999979019165,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9901999831199646,"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/adversarial-system","display_name":"Adversarial system","score":0.8817145824432373},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.751354992389679},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.7242543697357178},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5245523452758789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3508973717689514},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.33340930938720703}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8817145824432373},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.751354992389679},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.7242543697357178},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5245523452758789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3508973717689514},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.33340930938720703}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2105.09022","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.09022","pdf_url":"https://arxiv.org/pdf/2105.09022","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2105.09022","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2105.09022","pdf_url":"https://arxiv.org/pdf/2105.09022","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1494198834","https://openalex.org/W1586100143","https://openalex.org/W2070176749","https://openalex.org/W2640329709","https://openalex.org/W2696967604","https://openalex.org/W2890964092","https://openalex.org/W2901243971","https://openalex.org/W2916104401","https://openalex.org/W2963857521","https://openalex.org/W2981087920","https://openalex.org/W2984229499","https://openalex.org/W2985489290","https://openalex.org/W3006808893","https://openalex.org/W3007679772","https://openalex.org/W3010845645","https://openalex.org/W3013020904","https://openalex.org/W3015811740","https://openalex.org/W3015958938","https://openalex.org/W3084424094","https://openalex.org/W3093979537","https://openalex.org/W3151878189","https://openalex.org/W4288029451","https://openalex.org/W4293846201","https://openalex.org/W6634987543","https://openalex.org/W6739868092","https://openalex.org/W6769842499"],"related_works":["https://openalex.org/W1491159402","https://openalex.org/W66821593","https://openalex.org/W4297807400","https://openalex.org/W4313854686","https://openalex.org/W2249138175","https://openalex.org/W1521299571","https://openalex.org/W3162054169","https://openalex.org/W1813780412","https://openalex.org/W1516392727","https://openalex.org/W2140022733"],"abstract_inverted_index":{"In":[0,122],"authentication":[1,17,96],"scenarios,":[2],"applications":[3],"of":[4,133],"practical":[5,64],"speaker":[6,65],"verification":[7,66],"systems":[8],"usually":[9],"require":[10],"a":[11,15,27,55,73],"person":[12,159],"to":[13,30,81,87,113],"read":[14],"dynamic":[16],"text.":[18],"Previous":[19],"studies":[20],"played":[21,118],"an":[22],"audio":[23,40],"adversarial":[24,52,85],"example":[25],"as":[26,54,72],"digital":[28],"signal":[29],"perform":[31],"physical":[32,124],"attacks,":[33],"which":[34,109],"would":[35],"be":[36,88,114],"easily":[37],"rejected":[38],"by":[39,48,147],"replay":[41,154],"detection":[42,155],"modules.":[43],"This":[44],"work":[45],"shows":[46],"that":[47],"playing":[49],"our":[50],"crafted":[51],"perturbation":[53,86,112],"separate":[56],"source":[57],"when":[58],"the":[59,63,70,83,95,107,111,120,123,136,157],"adversary":[60,71],"is":[61,79],"speaking,":[62],"system":[67],"will":[68],"misjudge":[69],"target":[74],"speaker.":[75],"A":[76],"two-step":[77],"algorithm":[78,108],"proposed":[80],"optimize":[82],"universal":[84],"text-independent":[89],"and":[90],"has":[91],"little":[92],"effect":[93],"on":[94,141],"text":[97],"recognition.":[98],"We":[99],"also":[100],"estimated":[101],"room":[102],"impulse":[103],"response":[104],"(RIR)":[105],"in":[106],"allowed":[110],"effective":[115],"after":[116],"being":[117],"over":[119],"air.":[121],"experiment,":[125],"we":[126],"achieved":[127],"targeted":[128],"attacks":[129],"with":[130],"success":[131],"rate":[132,139],"100%,":[134],"while":[135],"word":[137],"error":[138],"(WER)":[140],"speech":[142],"recognition":[143],"was":[144],"only":[145],"increased":[146],"3.55%.":[148],"And":[149],"recorded":[150],"audios":[151],"could":[152],"pass":[153],"for":[156],"live":[158],"speaking.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
