Deep learning-based facial recognition (FR) models have demonstrated state-of-the-art
performance in the past few years, even when wearing protective medical face masks …

Modern face recognition systems widely use deep convolutional neural networks (DCNNs).
However, DCNNs are susceptible to adversarial examples, posing security risks to these …

Face authentication systems are widely employed in access control systems to ensure the
security of confidential facilities. Recent works have demonstrated their vulnerabilities to …

Face Recognition Systems (FRS) have increasingly integrated into critical applications,
including surveillance and user authentication, highlighting their pivotal role in modern …

Face recognition has achieved remarkable success due to the development of deep
convolutional neural networks (DCNNs). However, DCNNs are vulnerable to adversarial …

Biometric authentication has made great strides throughout the years thanks to better
hardware and software support. However, attackers are unrelenting in finding new ways to …

While neural networks are demonstrating excellent performance in a wide range of
applications, there has been a growing concern on their reliability and dependability. Similar …

Face verification (FV) using deep neural network models has made tremendous progress in
recent years, surpassing human accuracy and seeing deployment in various applications …

Facial recognition stands as a prevalent authen-tication solution within numerous biometric
authentication applications. As a crucial alternative means, adversarial attacks serve to …

Cybersecurity is rapidly evolving, necessitating inventive solutions for emerging challenges.
Deep Learning (DL), having demonstrated remarkable capabilities across various domains …