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 …

Abstract Generative Adversarial Networks (GAN) have led to the generation of very realistic
face images, which have been used in fake social media accounts and other disinformation …

Differences in forgery attributes of images generated in CNN-synthesized and image-editing
domains are large, and such differences make a unified image forgery detection and …

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 …

We propose an efficient algorithm to embed a given image into the latent space of StyleGAN.
This embedding enables semantic image editing operations that can be applied to existing …

In this paper, we propose a new approach to detect Deepfakes generated through the
generative adversarial network (GANs) model via an algorithm called DeepVision to analyze …

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 …

Face recognition has been successfully deployed in real-time applications, including secure
applications such as border control. The vulnerability of face recognition systems (FRSs) to …

Over the past two decades, biometric recognition has exploded into a plethora of different
applications around the globe. This proliferation can be attributed to the high levels of …

Face morphing attacks target to circumvent Face Recognition Systems (FRS) by employing
face images derived from multiple data subjects (eg, accomplices and malicious actors) …