{"id":"https://openalex.org/W2965039693","doi":"https://doi.org/10.1109/isba.2019.8778470","title":"Towards Reducing the Error Rates in Template Protection for Iris Recognition Using Custom Cuckoo Filters","display_name":"Towards Reducing the Error Rates in Template Protection for Iris Recognition Using Custom Cuckoo Filters","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2965039693","doi":"https://doi.org/10.1109/isba.2019.8778470","mag":"2965039693"},"language":"en","primary_location":{"id":"doi:10.1109/isba.2019.8778470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isba.2019.8778470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 5th International Conference on Identity, Security, and Behavior Analysis (ISBA)","raw_type":"proceedings-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/A5089066381","display_name":"Kiran Raja","orcid":"https://orcid.org/0000-0002-9489-5161"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kiran B. Raja","raw_affiliation_strings":["Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"R. Raghavendra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. Raghavendra","raw_affiliation_strings":["Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017716310","display_name":"Christoph Busch","orcid":"https://orcid.org/0000-0002-9159-2923"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christoph Busch","raw_affiliation_strings":["Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Biometrics Laboratory, NTNU - Gj\u00f8vik, Norway","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1683,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79073589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9890000224113464,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9501000046730042,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6737419962882996},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.6734949946403503},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.6357331871986389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5124405026435852},{"id":"https://openalex.org/keywords/cuckoo","display_name":"Cuckoo","score":0.4642411470413208},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4194890856742859},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41181641817092896},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3679562509059906},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34004804491996765},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.3076173663139343}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6737419962882996},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.6734949946403503},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.6357331871986389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124405026435852},{"id":"https://openalex.org/C2776810535","wikidata":"https://www.wikidata.org/wiki/Q26381","display_name":"Cuckoo","level":2,"score":0.4642411470413208},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4194890856742859},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41181641817092896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3679562509059906},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34004804491996765},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.3076173663139343},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C90856448","wikidata":"https://www.wikidata.org/wiki/Q431","display_name":"Zoology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isba.2019.8778470","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isba.2019.8778470","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 5th International Conference on Identity, Security, and Behavior Analysis (ISBA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W178227285","https://openalex.org/W1504113980","https://openalex.org/W1584467222","https://openalex.org/W1607101185","https://openalex.org/W1912154055","https://openalex.org/W1967373117","https://openalex.org/W1985110735","https://openalex.org/W1995054709","https://openalex.org/W2041942569","https://openalex.org/W2102525097","https://openalex.org/W2151148935","https://openalex.org/W2161087606","https://openalex.org/W2171431911","https://openalex.org/W2212252382","https://openalex.org/W2510055812","https://openalex.org/W2575866882","https://openalex.org/W2762129651","https://openalex.org/W2777595189","https://openalex.org/W2891497694","https://openalex.org/W2903082373","https://openalex.org/W2912601938","https://openalex.org/W4230888393","https://openalex.org/W6607197667"],"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/W3133795085"],"abstract_inverted_index":{"The":[0,89],"need":[1,110],"to":[2,82,104,156],"protect":[3],"biometric":[4,32],"data":[5],"within":[6],"iris":[7,27,122],"systems":[8],"has":[9],"resulted":[10],"in":[11,95,142,185,201],"a":[12,45,68,84,96,119,163],"number":[13],"of":[14,55,116,146,154,158,166],"template":[15,23,86,91,106,131,159],"protection":[16,24,87,92,107,132,160],"schemes.":[17],"A":[18],"primary":[19],"issue":[20],"with":[21,71],"current":[22],"schemes":[25,108],"for":[26,36,99],"recognition":[28],"is":[29,44],"the":[30,114,129,140,186,202],"unavoidable":[31],"error":[33],"rates,":[34],"i.e.,":[35],"any":[37],"given":[38],"False":[39,47],"Non-Match":[40],"Rate":[41,49,173],"(FNMR)":[42],"there":[43],"high":[46],"Match":[48,172],"(FMR),":[50],"especially":[51],"at":[52,149,177,193],"lower":[53,150],"values":[54],"FNMR.":[56],"In":[57],"this":[58,65],"work,":[59],"we":[60,124,138,169],"primarily":[61],"focus":[62],"on":[63,118,135,205],"addressing":[64],"problem":[66],"using":[67,75],"new":[69],"approach":[70,148],"Cuckoo":[72],"Filtering":[73],"simultaneously":[74],"both":[76],"stable":[77],"bits":[78,81],"and":[79,144,152,181,189,197],"discriminative":[80],"derive":[83],"stronger":[85],"scheme.":[88,161],"proposed":[90,147,167],"scheme":[93,133],"performs":[94],"robust":[97],"manner":[98],"various":[100],"configurations":[101,157],"as":[102],"compared":[103],"earlier":[105],"that":[109],"empirical":[111],"fine-tuning.":[112],"With":[113,162],"set":[115],"experiments":[117],"publicly":[120],"available":[121],"dataset,":[123],"benchmark":[125],"our":[126],"results":[127],"against":[128],"state-of-art":[130],"based":[134],"Bloom-Filters.":[136],"Specifically,":[137],"demonstrate":[139],"gain":[141],"performance":[143,155],"robustness":[145],"FNMR":[151],"invariance":[153],"specific":[164],"configuration":[165],"approach,":[168],"achieve":[170],"Genuine":[171],"(GMR)":[174],"=":[175,179,183,191,195,199],"100%":[176],"FMR":[178,194],"0:01%":[180,196],"EER":[182,198],"0%":[184],"best":[187],"case":[188,204],"GMR":[190],"98:44%":[192],"0:33%":[200],"worst":[203],"IITD":[206],"Iris":[207],"database.":[208]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}