Face Recognition Systems Under Morphing Attacks: A Survey

被引:115
|
作者
Scherhag, Ulrich [1 ]
Rathgeb, Christian [1 ,2 ]
Merkle, Johannes [2 ]
Breithaupt, Ralph [3 ]
Busch, Christoph [1 ]
机构
[1] Hsch Darmstadt, Da Sec Biometr & Internet Secur Res Grp, D-64295 Darmstadt, Germany
[2] Secunet Secur Networks AG, D-45138 Essen, Germany
[3] Fed Off Informat Secur BSI, D-53133 Bonn, Germany
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Biometrics; face morphing attack; face recognition; image morphing; morphing attack detection; IMAGE QUALITY ASSESSMENT; PERFORMANCE; PHOTOGRAPHS; DATABASE;
D O I
10.1109/ACCESS.2019.2899367
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, researchers found that the intended generalizability of (deep) face recognition systems increases their vulnerability against attacks. In particular, the attacks based on morphed face images pose a severe security risk to face recognition systems. In the last few years, the topic of (face) image morphing and automated morphing attack detection has sparked the interest of several research laboratories working in the field of biometrics and many different approaches have been published. In this paper, a conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications. In addition, technical considerations and tradeoffs of the surveyed methods are discussed along with open issues and challenges in the field.
引用
收藏
页码:23012 / 23026
页数:15
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