{"id":"https://openalex.org/W4281388433","doi":"https://doi.org/10.1145/3488932.3523257","title":"Artificial Intelligence Meets Kinesthetic Intelligence","display_name":"Artificial Intelligence Meets Kinesthetic Intelligence","publication_year":2022,"publication_date":"2022-05-24","ids":{"openalex":"https://openalex.org/W4281388433","doi":"https://doi.org/10.1145/3488932.3523257"},"language":"en","primary_location":{"id":"doi:10.1145/3488932.3523257","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488932.3523257","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488932.3523257","source":{"id":"https://openalex.org/S4363609011","display_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3488932.3523257","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042921547","display_name":"Fu Shen","orcid":"https://orcid.org/0000-0003-0364-7582"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shen Fu","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045811248","display_name":"Dong Qin","orcid":"https://orcid.org/0000-0003-1645-7892"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Qin","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018956193","display_name":"George T. Amariucai","orcid":"https://orcid.org/0000-0003-4471-6425"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Amariucai","raw_affiliation_strings":["Kansas State University, Manhattan, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079810736","display_name":"Daji Qiao","orcid":"https://orcid.org/0000-0002-3662-6481"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daji Qiao","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719924","display_name":"Yong Guan","orcid":"https://orcid.org/0000-0003-0445-1848"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Guan","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090743034","display_name":"Ann Smiley","orcid":null},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ann Smiley","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7587,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.86281805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1034","last_page":"1048"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11800","display_name":"User Authentication and Security Systems","score":1.0,"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"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9993000030517578,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8044045567512512},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6197683811187744},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6112895011901855},{"id":"https://openalex.org/keywords/kinesthetic-learning","display_name":"Kinesthetic learning","score":0.5903964042663574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5495535135269165},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.5341697335243225},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5198138952255249},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.15960410237312317}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8044045567512512},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6197683811187744},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6112895011901855},{"id":"https://openalex.org/C55457006","wikidata":"https://www.wikidata.org/wiki/Q3647098","display_name":"Kinesthetic learning","level":2,"score":0.5903964042663574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5495535135269165},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.5341697335243225},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5198138952255249},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.15960410237312317},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488932.3523257","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488932.3523257","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488932.3523257","source":{"id":"https://openalex.org/S4363609011","display_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3488932.3523257","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3488932.3523257","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3488932.3523257","source":{"id":"https://openalex.org/S4363609011","display_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","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":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6899999976158142,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3762898675","display_name":"SBE: Small: Continuous Human-User Authentication by Induced Procedural Visual-Motor Biometrics","funder_award_id":"1619201","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281388433.pdf","grobid_xml":"https://content.openalex.org/works/W4281388433.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W561687969","https://openalex.org/W895648301","https://openalex.org/W1488792108","https://openalex.org/W1584943908","https://openalex.org/W1975994995","https://openalex.org/W1977470670","https://openalex.org/W1982112776","https://openalex.org/W1998448825","https://openalex.org/W2000943643","https://openalex.org/W2010019780","https://openalex.org/W2012029720","https://openalex.org/W2026128819","https://openalex.org/W2030390520","https://openalex.org/W2036501403","https://openalex.org/W2054177909","https://openalex.org/W2092988036","https://openalex.org/W2093197020","https://openalex.org/W2109294345","https://openalex.org/W2120036128","https://openalex.org/W2131976234","https://openalex.org/W2144862309","https://openalex.org/W2155628890","https://openalex.org/W2169360434","https://openalex.org/W2340640534","https://openalex.org/W2402857500","https://openalex.org/W2435639410","https://openalex.org/W2514604835","https://openalex.org/W2539318522","https://openalex.org/W2598853221","https://openalex.org/W2615792717","https://openalex.org/W2734150319","https://openalex.org/W2781498977","https://openalex.org/W2787721734","https://openalex.org/W2889546917","https://openalex.org/W2956162661","https://openalex.org/W2962823371","https://openalex.org/W2964186248","https://openalex.org/W2997488226","https://openalex.org/W3004251986","https://openalex.org/W3041082021","https://openalex.org/W3047923360","https://openalex.org/W3055637487","https://openalex.org/W3169964936","https://openalex.org/W4206029699","https://openalex.org/W4238066225","https://openalex.org/W6602820859","https://openalex.org/W6718290646"],"related_works":["https://openalex.org/W3111440524","https://openalex.org/W2558272010","https://openalex.org/W2731243571","https://openalex.org/W4385174651","https://openalex.org/W3162087156","https://openalex.org/W1597792207","https://openalex.org/W2133182130","https://openalex.org/W2921166921","https://openalex.org/W3104966193","https://openalex.org/W2123843216"],"abstract_inverted_index":{"Current":[0],"mainstream":[1],"biometric":[2,28],"user":[3,55,68,84,95],"authentication":[4,96,158,190],"approaches":[5],"are":[6,199],"based":[7],"on":[8,118],"passive":[9],"measurements":[10],"of":[11,32,49,64,73,206,232,239,252],"the":[12,43,53,65,79,83,111,130,150,170,189,203,210,237,240,250],"subject's":[13],"characteristics,":[14],"and":[15,126,148,196],"usually":[16],"come":[17],"with":[18,78,153],"less-than-satisfactory":[19],"accuracy.":[20],"This":[21],"paper":[22,44],"takes":[23],"a":[24,34,40,46,61,71,93,135,174,245,256],"unique":[25],"approach":[26,152,167,187],"to":[27,38,59,76,86,110,122,129,201,248],"authentication.":[29],"Specifically,":[30],"instead":[31],"training":[33],"machine":[35,103,208],"learning":[36,125],"algorithm":[37],"recognize":[39],"legitimate":[41,54,195],"user,":[42],"proposes":[45],"hybrid":[47],"type":[48],"training,":[50],"in":[51,92,98,163,172,254],"which":[52,81,99,173,234],"is":[56,178],"also":[57,183,218],"trained":[58,200],"use":[60],"customized":[62,102,207],"instance":[63,205],"machine.":[66],"The":[67],"thus":[69],"achieves":[70],"level":[72],"artificially-induced":[74],"expertise":[75,227],"interact":[77],"machine,":[80],"makes":[82],"easier":[85],"recognize.":[87],"We":[88,133,160],"implement":[89],"this":[90,146],"concept":[91],"mouse-based":[94,157],"system,":[97],"we":[100,217,243],"produce":[101],"instances":[104],"by":[105],"introducing":[106],"an":[107],"angle":[108,213],"offset":[109],"standard":[112],"mouse.":[113,132],"Human":[114],"subjects":[115,144],"then":[116],"rely":[117],"their":[119,225],"kinesthetic":[120],"intelligence":[121],"achieve":[123],"motor":[124],"visual-motor":[127],"adaptation":[128],"modified":[131],"design":[134],"7-week":[136],"IRB-approved":[137],"experiment,":[138],"collect":[139],"data":[140],"from":[141],"18":[142],"human":[143],"over":[145],"period,":[147],"evaluate":[149],"proposed":[151,257],"two":[154],"existing":[155],"state-of-the-art":[156],"schemes.":[159],"find":[161],"that,":[162],"both":[164,194],"schemes,":[165],"our":[166,186],"significantly":[168],"outperforms":[169],"baseline":[171],"regular":[175],"unaltered":[176],"mouse":[177,212],"used.":[179],"Somewhat":[180],"surprisingly,":[181],"results":[182],"show":[184],"that":[185,220],"improves":[188],"performance":[191],"even":[192,228],"when":[193],"non-legitimate":[197],"users":[198,221,253],"exactly":[202],"same":[204,211],"(i.e.,":[209],"offset).":[214],"In":[215],"addition,":[216],"observe":[219],"can":[222],"generally":[223],"maintain":[224],"learned":[226],"after":[229],"one":[230],"week":[231],"washout,":[233],"further":[235],"demonstrates":[236],"practicality":[238],"approach.":[241],"Finally,":[242],"present":[244],"practical":[246],"strategy":[247],"manage":[249],"enrollment":[251],"such":[255],"system.":[258]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
