Spoofing Face Recognition With 3D Masks

Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks (presentation attacks) is still an open security issue in biometrics domain and among all biometric traits, face is exposed to the most seri...

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Vydáno v:	IEEE transactions on information forensics and security Ročník 9; číslo 7; s. 1084 - 1097
Hlavní autoři:	Erdogmus, Nesli, Marcel, Sebastien
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.07.2014 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Applied sciences Artificial intelligence Biometrics Computer aided design Computer information security Computer science; control theory; systems Computer systems and distributed systems. User interface Exact sciences and technology Face Face recognition Information systems. Data bases Masks Materials Memory organisation. Data processing Pattern recognition. Digital image processing. Computational geometry Software Solid modeling Spoofing Three dimensional Three-dimensional displays Two dimensional Videos Spoofing face recognition mask attack presentation attack Biometrics Computer vision Image processing Face recognition Distributed database Countermeasurement Mask Spoofing attack Video cameras Vulnerability Texture Image reconstruction Facies Rapid prototyping Tridimensional image Safety Computer aided design Computer attack Flatness Intrusion detection systems
ISSN:	1556-6013, 1556-6021
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Abstract	Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks (presentation attacks) is still an open security issue in biometrics domain and among all biometric traits, face is exposed to the most serious threat, since it is particularly easy to access and reproduce. In this paper, many different types of face spoofing attacks have been examined and various algorithms have been proposed to detect them. Mainly focusing on 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices, a significant portion of these studies ground their arguments on the flatness of the spoofing material in front of the sensor. However, with the advancements in 3D reconstruction and printing technologies, this assumption can no longer be maintained. In this paper, we aim to inspect the spoofing potential of subject-specific 3D facial masks for different recognition systems and address the detection problem of this more complex attack type. In order to assess the spoofing performance of 3D masks against 2D, 2.5D, and 3D face recognition and to analyze various texture-based countermeasures using both 2D and 2.5D data, a parallel study with comprehensive experiments is performed on two data sets: the Morpho database which is not publicly available and the newly distributed 3D mask attack database.
AbstractList	Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks (presentation attacks) is still an open security issue in biometrics domain and among all biometric traits, face is exposed to the most serious threat, since it is particularly easy to access and reproduce. In this paper, many different types of face spoofing attacks have been examined and various algorithms have been proposed to detect them. Mainly focusing on 2D attacks forged by displaying printed photos or replaying recorded videos on mobile devices, a significant portion of these studies ground their arguments on the flatness of the spoofing material in front of the sensor. However, with the advancements in 3D reconstruction and printing technologies, this assumption can no longer be maintained. In this paper, we aim to inspect the spoofing potential of subject-specific 3D facial masks for different recognition systems and address the detection problem of this more complex attack type. In order to assess the spoofing performance of 3D masks against 2D, 2.5D, and 3D face recognition and to analyze various texture-based countermeasures using both 2D and 2.5D data, a parallel study with comprehensive experiments is performed on two data sets: the Morpho database which is not publicly available and the newly distributed 3D mask attack database.
Author	Marcel, Sebastien Erdogmus, Nesli
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Keywords	Spoofing face recognition mask attack presentation attack Biometrics Computer vision Image processing Face recognition Distributed database Countermeasurement Mask Spoofing attack Video cameras Vulnerability Texture Image reconstruction Facies Rapid prototyping Tridimensional image Safety Computer aided design Computer attack Flatness Intrusion detection systems
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Snippet	Spoofing is the act of masquerading as a valid user by falsifying data to gain an illegitimate access. Vulnerability of recognition systems to spoofing attacks...
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SubjectTerms	Applied sciences Artificial intelligence Biometrics Computer aided design Computer information security Computer science; control theory; systems Computer systems and distributed systems. User interface Exact sciences and technology Face Face recognition Information systems. Data bases Masks Materials Memory organisation. Data processing Pattern recognition. Digital image processing. Computational geometry Software Solid modeling Spoofing Three dimensional Three-dimensional displays Two dimensional Videos
Title	Spoofing Face Recognition With 3D Masks
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