Face Recognition Systems Under Morphing Attacks: A Survey
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)...
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doaj-a6338874086f41d2851db5fce7002cf02021-03-29T22:03:29ZengIEEEIEEE Access2169-35362019-01-017230122302610.1109/ACCESS.2019.28993678642312Face Recognition Systems Under Morphing Attacks: A SurveyUlrich Scherhag0https://orcid.org/0000-0002-6280-048XChristian Rathgeb1Johannes Merkle2Ralph Breithaupt3Christoph Busch4da/sec–Biometrics and Internet Security Research Group, Hochschule Darmstadt, Darmstadt, Germanyda/sec–Biometrics and Internet Security Research Group, Hochschule Darmstadt, Darmstadt, Germanysecunet Security Networks AG, Essen, GermanyFederal Office of Information Security (BSI), Bonn, Germanyda/sec–Biometrics and Internet Security Research Group, Hochschule Darmstadt, Darmstadt, GermanyRecently, 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.https://ieeexplore.ieee.org/document/8642312/Biometricsface morphing attackface recognitionimage morphingmorphing attack detection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ulrich Scherhag Christian Rathgeb Johannes Merkle Ralph Breithaupt Christoph Busch |
spellingShingle |
Ulrich Scherhag Christian Rathgeb Johannes Merkle Ralph Breithaupt Christoph Busch Face Recognition Systems Under Morphing Attacks: A Survey IEEE Access Biometrics face morphing attack face recognition image morphing morphing attack detection |
author_facet |
Ulrich Scherhag Christian Rathgeb Johannes Merkle Ralph Breithaupt Christoph Busch |
author_sort |
Ulrich Scherhag |
title |
Face Recognition Systems Under Morphing Attacks: A Survey |
title_short |
Face Recognition Systems Under Morphing Attacks: A Survey |
title_full |
Face Recognition Systems Under Morphing Attacks: A Survey |
title_fullStr |
Face Recognition Systems Under Morphing Attacks: A Survey |
title_full_unstemmed |
Face Recognition Systems Under Morphing Attacks: A Survey |
title_sort |
face recognition systems under morphing attacks: a survey |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
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. |
topic |
Biometrics face morphing attack face recognition image morphing morphing attack detection |
url |
https://ieeexplore.ieee.org/document/8642312/ |
work_keys_str_mv |
AT ulrichscherhag facerecognitionsystemsundermorphingattacksasurvey AT christianrathgeb facerecognitionsystemsundermorphingattacksasurvey AT johannesmerkle facerecognitionsystemsundermorphingattacksasurvey AT ralphbreithaupt facerecognitionsystemsundermorphingattacksasurvey AT christophbusch facerecognitionsystemsundermorphingattacksasurvey |
_version_ |
1724192300148457472 |