Juvenile Morph Dataset: A Study of Attack Detectability and Recognition Vulnerability

Kelsey O'Haire, Sobhan Soleymani, Samuel Price, N. Nasrabadi
{"title":"Juvenile Morph Dataset: A Study of Attack Detectability and Recognition Vulnerability","authors":"Kelsey O'Haire, Sobhan Soleymani, Samuel Price, N. Nasrabadi","doi":"10.1109/HST56032.2022.10025448","DOIUrl":null,"url":null,"abstract":"A morph is an image of an ambiguous subject generated by combining multiple individuals. The morphed image can be submitted to a facial recognition system and erroneously verified with the contributing bad actors. When submitted as a passport image, a morphed face poses a national security threat because a passport can then be shared between the individuals. As morphed images become easier to generate, it is vital that the research community expands available datasets in order to contentiously improve current technology. Children are a challenging paradigm for facial recognition systems and morphing children takes advantage of this disparity. In this paper, we morph juvenile faces in order to create a unique, high-quality dataset to challenge FRS. To the best of our knowledge, this is the first study on the generation and evaluation of juvenile morphed faces. The evaluation of the generated morphed juvenile dataset is performed in terms of vulnerability analysis and presentation attack error rates.","PeriodicalId":162426,"journal":{"name":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Technologies for Homeland Security (HST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HST56032.2022.10025448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

A morph is an image of an ambiguous subject generated by combining multiple individuals. The morphed image can be submitted to a facial recognition system and erroneously verified with the contributing bad actors. When submitted as a passport image, a morphed face poses a national security threat because a passport can then be shared between the individuals. As morphed images become easier to generate, it is vital that the research community expands available datasets in order to contentiously improve current technology. Children are a challenging paradigm for facial recognition systems and morphing children takes advantage of this disparity. In this paper, we morph juvenile faces in order to create a unique, high-quality dataset to challenge FRS. To the best of our knowledge, this is the first study on the generation and evaluation of juvenile morphed faces. The evaluation of the generated morphed juvenile dataset is performed in terms of vulnerability analysis and presentation attack error rates.
未成年变形数据集:攻击可检测性与识别漏洞研究
变形是由多个个体组合而成的模糊主体的图像。变形后的图像可以提交给人脸识别系统,并与不良行为者进行错误的验证。当以护照图像的形式提交时,变形的脸会对国家安全构成威胁,因为护照可以在个人之间共享。随着变形图像变得更容易生成,为了不断改进现有技术,研究团体扩展可用数据集是至关重要的。对于面部识别系统来说,儿童是一个具有挑战性的范例,变形儿童利用了这一差异。在本文中,我们对未成年人的面孔进行变形,以创建一个独特的、高质量的数据集来挑战FRS。据我们所知,这是第一个关于未成年人变形面孔的生成和评估的研究。根据漏洞分析和表示攻击错误率对生成的变形少年数据集进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信