Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

Deepfakes present an emerging threat in cyberspace. Recent developments in machine
learning make deepfakes highly believable, and very difficult to differentiate between what is …

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

A face morphing attack image can be verified to multiple identities, making this attack a
major vulnerability to processes based on identity verification, such as border checks …

Face recognition systems (FRS) are vulnerable to different kinds of attacks. Morphing attack
combines multiple face images to obtain a single face image that can verify equally against …

To strengthen the security of face recognition systems to morphing attacks (MAs), many
countermeasures were proposed. However, in the existing face morphing attack detection …

Semantic face image manipulation has received increasing attention in recent years.
StyleGAN-based approaches to face morphing are among the leading techniques; however …

Face recognition has been widely used for identity verification both in supervised and
unsupervised access control applications. The advancement in deep neural networks has …

Digital manipulation has become a thriving topic in the last few years, especially after the
popularity of the term DeepFakes. This chapter introduces the prominent digital …

Morphing attacks are based on the technique of digitally fusing two (or more) face images
into one, with the final visage resembling the contributing faces. Morphed images not only …