{"id":"https://openalex.org/W2149064334","doi":"https://doi.org/10.1109/tifs.2011.2108288","title":"How to Generate Spoofed Irises From an Iris Code Template","display_name":"How to Generate Spoofed Irises From an Iris Code Template","publication_year":2011,"publication_date":"2011-01-28","ids":{"openalex":"https://openalex.org/W2149064334","doi":"https://doi.org/10.1109/tifs.2011.2108288","mag":"2149064334"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2011.2108288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2011.2108288","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","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/A5009792021","display_name":"Shreyas Venugopalan","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shreyas Venugopalan","raw_affiliation_strings":["Cylab Biometrics Center, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Cylab Biometrics Center, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057959136","display_name":"Marios Savvides","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marios Savvides","raw_affiliation_strings":["Cylab Biometrics Center, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Cylab Biometrics Center, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009792021"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":10.5968,"has_fulltext":false,"cited_by_count":127,"citation_normalized_percentile":{"value":0.98941384,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"385","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"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":0.9937000274658203,"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/T13192","display_name":"Forensic Fingerprint Detection Methods","score":0.9782000184059143,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.9172148108482361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8492748737335205},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.7888533473014832},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.7609507441520691},{"id":"https://openalex.org/keywords/hamming-distance","display_name":"Hamming distance","score":0.644449770450592},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6147384643554688},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6087721586227417},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.538343071937561},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5145970582962036},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49802064895629883},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4437206983566284},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08826351165771484}],"concepts":[{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.9172148108482361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8492748737335205},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.7888533473014832},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7609507441520691},{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.644449770450592},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6147384643554688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6087721586227417},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.538343071937561},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5145970582962036},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49802064895629883},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4437206983566284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08826351165771484},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2011.2108288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2011.2108288","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"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 Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1604151639","https://openalex.org/W1991366937","https://openalex.org/W2025546194","https://openalex.org/W2028999707","https://openalex.org/W2031996436","https://openalex.org/W2051387832","https://openalex.org/W2090425678","https://openalex.org/W2114415923","https://openalex.org/W2124890704","https://openalex.org/W2127392200","https://openalex.org/W2133555949","https://openalex.org/W2151148935","https://openalex.org/W2159322247","https://openalex.org/W2167141450","https://openalex.org/W2170096609","https://openalex.org/W2606090080","https://openalex.org/W4254044281","https://openalex.org/W6635980354","https://openalex.org/W6684705476","https://openalex.org/W6940683317"],"related_works":["https://openalex.org/W2162640687","https://openalex.org/W2018223046","https://openalex.org/W2151970936","https://openalex.org/W2759939383","https://openalex.org/W2294693339","https://openalex.org/W2355560018","https://openalex.org/W2147209541","https://openalex.org/W4231710054","https://openalex.org/W2557390811","https://openalex.org/W2169064741"],"abstract_inverted_index":{"Biometrics":[0],"has":[1],"gained":[2],"a":[3,11,87,95,161,191],"lot":[4],"of":[5,93,126,150,182,220,242],"attention":[6],"over":[7],"recent":[8],"years":[9],"as":[10,124,141],"way":[12],"to":[13,52,81,112,157,196,230,234],"identify":[14],"individuals.":[15],"Of":[16],"all":[17],"biometrics-based":[18],"techniques,":[19],"the":[20,46,91,120,127,147,151,169,178,183,238,243],"iris-pattern-based":[21],"systems":[22,139],"have":[23],"recently":[24],"shown":[25],"very":[26,202],"high":[27],"accuracies":[28],"in":[29,75],"verifying":[30],"an":[31,53,113],"individual's":[32],"identity.":[33],"The":[34],"premise":[35],"here":[36,226],"is":[37,63,71,110,224],"that":[38,66,125,154,166],"iris":[39,47,68,84,100,114,129,153,184,194,213],"patterns":[40],"are":[41],"unique":[42],"across":[43],"people.":[44],"Only":[45],"bit":[48,69,101],"code":[49,70],"template":[50],"specific":[51],"individual":[54],"need":[55],"be":[56],"stored":[57],"for":[58,86,90],"future":[59],"identity":[60],"verification.":[61],"It":[62],"generally":[64],"accepted":[65],"this":[67,76,99,107,132,232],"unidentifiable":[72],"data.":[73],"However,":[74],"work,":[77],"we":[78,155,176,228],"explore":[79],"methods":[80],"generate":[82,119],"alternate":[83],"textures":[85],"given":[88],"person":[89],"purpose":[92],"bypassing":[94],"system":[96,215],"based":[97],"on":[98],"code.":[102],"We":[103,187],"show":[104],"that,":[105],"if":[106],"spoof":[108,197],"texture":[109,149,195],"presented":[111,225],"recognition":[115,214,244],"system,":[116],"it":[117],"will":[118],"same":[121],"score":[122,165,171],"response":[123],"original":[128],"texture.":[130],"Hence,":[131],"approach":[133,174],"can":[134,209],"bypass":[135],"filter-based":[136],"feature":[137,179,239],"extraction":[138,180,240],"(such":[140],"Daugman":[142],"style":[143],"systems)":[144],"without":[145],"using":[146],"actual":[148],"target":[152],"want":[156],"spoof,":[158],"by":[159,211,216],"obtaining":[160],"hamming":[162],"distance":[163],"match":[164],"falls":[167],"within":[168,190],"authentic":[170],"range.":[172],"This":[173],"assumes":[175],"know":[177],"mechanism":[181],"matching":[185],"scheme.":[186],"embed":[188],"features":[189],"person's":[192,199],"natural":[193],"another":[198],"iris.":[200],"A":[201],"convincing":[203],"preliminary":[204],"investigation":[205],"into":[206,237],"how":[207],"one":[208],"get":[210],"any":[212],"synthesizing":[217],"various":[218],"levels":[219],"\u201cnatural\u201d":[221],"looking":[222],"irises":[223],"and":[227],"hope":[229],"use":[231],"knowledge":[233],"build":[235],"countermeasures":[236],"scheme":[241],"module.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":7}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}