{"id":"https://openalex.org/W3195948749","doi":"https://doi.org/10.1109/jiot.2021.3097266","title":"Efficient and Privacy-Preserving Speaker Recognition for Cybertwin-Driven 6G","display_name":"Efficient and Privacy-Preserving Speaker Recognition for Cybertwin-Driven 6G","publication_year":2021,"publication_date":"2021-08-24","ids":{"openalex":"https://openalex.org/W3195948749","doi":"https://doi.org/10.1109/jiot.2021.3097266","mag":"3195948749"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2021.3097266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2021.3097266","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-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/A5100350266","display_name":"Qi Li","orcid":"https://orcid.org/0000-0003-1720-2664"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["School of Computer Science, University of Guelph, Guelph, Canada"],"raw_orcid":"https://orcid.org/0000-0003-1720-2664","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083787204","display_name":"Xiaodong Lin","orcid":"https://orcid.org/0000-0001-8916-6645"},"institutions":[{"id":"https://openalex.org/I79817857","display_name":"University of Guelph","ror":"https://ror.org/01r7awg59","country_code":"CA","type":"education","lineage":["https://openalex.org/I79817857"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xiaodong Lin","raw_affiliation_strings":["School of Computer Science, University of Guelph, Guelph, Canada"],"raw_orcid":"https://orcid.org/0000-0001-8916-6645","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Guelph, Guelph, Canada","institution_ids":["https://openalex.org/I79817857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79817857"],"apc_list":null,"apc_paid":null,"fwci":1.0919,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81676164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":"22","first_page":"16195","last_page":"16206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9993000030517578,"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":0.9993000030517578,"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/T10828","display_name":"Biometric Identification and Security","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.8032264113426208},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.6436399221420288},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5617243647575378},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5605273246765137},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.4785269498825073},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.4317631721496582},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4172631502151489},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3716837167739868},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3512687087059021},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3432275652885437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2767831087112427},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2761036455631256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2535587251186371}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8032264113426208},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.6436399221420288},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5617243647575378},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5605273246765137},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.4785269498825073},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.4317631721496582},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4172631502151489},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3716837167739868},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3512687087059021},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3432275652885437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2767831087112427},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2761036455631256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2535587251186371}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2021.3097266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2021.3097266","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1486770802","https://openalex.org/W2005308782","https://openalex.org/W2028662467","https://openalex.org/W2039057510","https://openalex.org/W2041480327","https://openalex.org/W2053826825","https://openalex.org/W2054701320","https://openalex.org/W2061533153","https://openalex.org/W2080818301","https://openalex.org/W2096521846","https://openalex.org/W2096733369","https://openalex.org/W2102415185","https://openalex.org/W2121812409","https://openalex.org/W2126933852","https://openalex.org/W2146860676","https://openalex.org/W2150769028","https://openalex.org/W2294473867","https://openalex.org/W2344822617","https://openalex.org/W2395750323","https://openalex.org/W2494605628","https://openalex.org/W2612434969","https://openalex.org/W2612895160","https://openalex.org/W2726515241","https://openalex.org/W2746471976","https://openalex.org/W2748466034","https://openalex.org/W2748488820","https://openalex.org/W2783108448","https://openalex.org/W2790376259","https://openalex.org/W2791874343","https://openalex.org/W2798724621","https://openalex.org/W2898143174","https://openalex.org/W2900688537","https://openalex.org/W2956804760","https://openalex.org/W2969985801","https://openalex.org/W2977364006","https://openalex.org/W2979157532","https://openalex.org/W2991103840","https://openalex.org/W3021440442","https://openalex.org/W3099206234","https://openalex.org/W4234330420","https://openalex.org/W4244171381","https://openalex.org/W6674194619","https://openalex.org/W6704529918"],"related_works":["https://openalex.org/W1620589732","https://openalex.org/W3154024765","https://openalex.org/W1988301709","https://openalex.org/W2778699561","https://openalex.org/W2370902379","https://openalex.org/W2799647799","https://openalex.org/W2248014602","https://openalex.org/W2105110288","https://openalex.org/W2776948974","https://openalex.org/W2946614119"],"abstract_inverted_index":{"With":[0,108],"the":[1,14,31,35,57,68,81,110,122,129,141,165,173,180],"introduction":[2],"of":[3,37,83,168],"cybertwin,":[4],"a":[5,224],"new":[6],"approach":[7],"to":[8,24,56,100,164],"represent":[9],"human":[10],"or":[11],"things":[12],"in":[13,30,45,79,105,137,223],"cyberspace,":[15],"it":[16],"is":[17,103,213],"foreseeable":[18],"that":[19,193,211],"vehicles":[20],"will":[21,41],"be":[22,42,114,161,220],"able":[23],"offer":[25],"more":[26,28],"and":[27,59,64,91,140,155,187,205,216,218],"services":[29],"future.":[32],"Naturally,":[33],"considering":[34],"safety":[36],"drivers,":[38],"speaker":[39,73,93,111,157],"recognition":[40,49,74,94,158],"widely":[43],"used":[44],"vehicle":[46,228],"scenarios.":[47],"Speaker":[48],"technologies":[50,75],"are":[51,147],"experiencing":[52],"increasing":[53],"popularity":[54],"due":[55],"unique":[58],"indissoluble":[60],"link":[61],"between":[62],"individuals":[63],"their":[65],"voices.":[66],"However,":[67],"coming":[69],"cybertwin-driven":[70,97,226],"6G":[71,227],"brings":[72],"unprecedented":[76],"challenges,":[77,88],"especially":[78],"preventing":[80],"disclosure":[82],"voiceprint.":[84],"To":[85],"address":[86],"these":[87,151],"an":[89],"efficient":[90,154],"privacy-preserving":[92],"scheme":[95,159],"for":[96],"6G,":[98],"referred":[99],"as":[101,184],"NEATEN,":[102,109],"proposed":[104],"this":[106],"article.":[107],"identity":[112],"can":[113,160,195,219],"recognized":[115],"at":[116],"multiple":[117],"security":[118,199],"levels":[119],"without":[120],"leaking":[121],"voiceprint":[123,134],"data.":[124],"More":[125],"concretely,":[126],"based":[127,171],"on":[128,172,179,203],"random":[130],"projection":[131],"data":[132,207],"perturbation,":[133],"perturbation":[135],"algorithms":[136],"two":[138],"phases":[139],"corresponding":[142],"ciphertext-based":[143],"similarity":[144],"computation":[145],"algorithm":[146],"proposed.":[148],"By":[149],"using":[150],"algorithms,":[152],"our":[153],"accurate":[156,215],"achieved.":[162],"Orthogonal":[163],"previous":[166],"works":[167],"biometric":[169],"identification":[170],"Euclidean":[174],"distance,":[175,182],"NEATEN":[176,194,212],"makes":[177],"progress":[178],"non-Euclidean":[181],"such":[183],"cosine":[185],"distance":[186],"complicated":[188],"distance.":[189],"Detailed":[190],"analysis":[191],"shows":[192],"resist":[196],"various":[197],"known":[198],"threats.":[200],"Experiments":[201],"conducted":[202],"TIMIT":[204],"Voxceleb":[206],"sets":[208],"have":[209],"demonstrated":[210],"highly":[214],"efficient,":[217],"flexibly":[221],"deployed":[222],"real":[225],"environment.":[229]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}