Generative Adversarial Networks (GANs) have promoted a variety of applications in
computer vision and natural language processing, among others, due to its generative …

Over the past years, deep learning capabilities and the availability of large-scale training
datasets advanced rapidly, leading to breakthroughs in face recognition accuracy. However …

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

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 …

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

The main question this work aims at answering is:" can morphing attack detection (MAD)
solutions be successfully developed based on synthetic data?". Towards that, this work …

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 …

Speech deepfakes are artificial voices generated by machine learning models. Previous
literature has highlighted deepfakes as one of the biggest security threats arising from …

The primary objective of face morphing is to com-bine face images of different data subjects
(eg an malicious actor and an accomplice) to generate a face image that can be equally …