On the vulnerability of face recognition systems to spoofing mask attacks

There are several types of spoofing attacks to face recognition systems such as photograph, video or mask attacks. To the best of our knowledge, the impact of mask spoofing on face recognition has not been analyzed yet. The reason for this delay is mainly due to the unavailability of public mask attacks databases. In this study, we use a 2D+3D mask database which was prepared for a research project in which the authors are all involved. This paper provides new results by demonstrating the impact of mask attacks on 2D, 2.5D and 3D face recognition systems. The results show that face recognition systems are vulnerable to mask attacks, thus countermeasures have to be developed to reduce the impact of mask attacks on face recognition. The results also show that 2D texture analysis provides more information than 3D face shape analysis in order to develop a countermeasure against high-quality mask attacks.