{"title":"基于一套独特手指静脉识别算法的漏洞评估与表示攻击检测","authors":"Johannes Schuiki, Georg Wimmer, A. Uhl","doi":"10.1109/IJCB52358.2021.9484351","DOIUrl":null,"url":null,"abstract":"The act of presenting a forged biometric sample to a bio-metric capturing device is referred to as presentation at-tack. During the last decade this type of attack has been addressed for various biometric traits and is still a widely researched topic. This study follows the idea from a previously published work which employs the usage of twelve algorithms for finger vein recognition in order to perform an extensive vulnerability analysis on a presentation at-tack database. The present work adopts this idea and examines two already existing finger vein presentation attack databases with the goal to evaluate how hazardous these presentation attacks are from a wider perspective. Additionally, this study shows that by combining the matching scores from different algorithms, presentation attack detection can be achieved.","PeriodicalId":175984,"journal":{"name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Vulnerability Assessment and Presentation Attack Detection Using a Set of Distinct Finger Vein Recognition Algorithms\",\"authors\":\"Johannes Schuiki, Georg Wimmer, A. Uhl\",\"doi\":\"10.1109/IJCB52358.2021.9484351\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The act of presenting a forged biometric sample to a bio-metric capturing device is referred to as presentation at-tack. During the last decade this type of attack has been addressed for various biometric traits and is still a widely researched topic. This study follows the idea from a previously published work which employs the usage of twelve algorithms for finger vein recognition in order to perform an extensive vulnerability analysis on a presentation at-tack database. The present work adopts this idea and examines two already existing finger vein presentation attack databases with the goal to evaluate how hazardous these presentation attacks are from a wider perspective. Additionally, this study shows that by combining the matching scores from different algorithms, presentation attack detection can be achieved.\",\"PeriodicalId\":175984,\"journal\":{\"name\":\"2021 IEEE International Joint Conference on Biometrics (IJCB)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Joint Conference on Biometrics (IJCB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCB52358.2021.9484351\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Joint Conference on Biometrics (IJCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCB52358.2021.9484351","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vulnerability Assessment and Presentation Attack Detection Using a Set of Distinct Finger Vein Recognition Algorithms
The act of presenting a forged biometric sample to a bio-metric capturing device is referred to as presentation at-tack. During the last decade this type of attack has been addressed for various biometric traits and is still a widely researched topic. This study follows the idea from a previously published work which employs the usage of twelve algorithms for finger vein recognition in order to perform an extensive vulnerability analysis on a presentation at-tack database. The present work adopts this idea and examines two already existing finger vein presentation attack databases with the goal to evaluate how hazardous these presentation attacks are from a wider perspective. Additionally, this study shows that by combining the matching scores from different algorithms, presentation attack detection can be achieved.