Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

When used maliciously, deepfake can pose detrimental implications to political and social
forces including reducing public trust in institutions, damaging the reputation of prominent …

It is becoming increasingly easy to automatically replace a face of one person in a video with
the face of another person by using a pre-trained generative adversarial network (GAN) …

Recently, researchers found that the intended generalizability of (deep) face recognition
systems increases their vulnerability against attacks. In particular, the attacks based on …

It is becoming increasingly easy to automatically replace a face of one person in a video with
the face of another person by using a pre-trained generative adversarial network (GAN) …

The vulnerability of facial recognition systems to face morphing attacks is well known. Many
different approaches for morphing attack detection (MAD) have been proposed in the …

Recent research found that attacks based on morphed face images, ie, morphing attacks,
pose a severe security risk to face recognition systems. A reliable morphing attack detection …

Recent research has demonstrated that lip-based speaker authentication systems can not
only achieve good authentication performance but also guarantee liveness. However, with …

Deep neural network (DNN) architecture based models have high expressive power and
learning capacity. However, they are essentially a black box method since it is not easy to …

Deepfake videos, where a person's face is automatically swapped with a face of someone
else, are becoming easier to generate with more realistic results. In response to the threat …