Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

The vulnerability of face recognition systems to presentation attacks (also known as direct
attacks or spoof attacks) has received a great deal of interest from the biometric community …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

Techniques for creating and manipulating multimedia information have progressed to the
point where they can now ensure a high degree of realism. DeepFake is a generative deep …

Given the ubiquity of deep neural networks, it is important that these models do not reveal
information about sensitive data that they have been trained on. In model inversion attacks …

The vulnerabilities of face-based biometric systems to presentation attacks have been finally
recognized but yet we lack generalized software-based face presentation attack detection …

Research on non-intrusive software-based face spoofing detection schemes has been
mainly focused on the analysis of the luminance information of the face images, hence …

With the wide deployment of the face recognition systems in applications from deduplication
to mobile device unlocking, security against the face spoofing attacks requires increased …

With the powerful deep network architectures, such as generative adversarial networks, one
can easily generate photorealistic images. Although the generated images are not …

The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …