This paper presents a secure face recognition system with advanced template protection
schemes for Cyber–Physical–Social Services (CPSS). The implementation of the proposed …

Contemporary face recognition systems use feature templates extracted from face images to
identify persons. To enhance privacy, face template protection techniques are widely …

Biometric technology is rapidly growing due to the urgent need to secure people's
properties, from goods to information, in the overwhelming digital technology proliferation in …

This paper proposes PolyProtect, a method for protecting the sensitive face embeddings that
are used to represent people's faces in neural-network-based face verification systems …

Cancellable biometrics is essential for preserving sensitive biometric information from
potential exposure. Existing studies usually convert real-valued biometric vectors into …

Convolutional neural networks have made remarkable progress in the face recognition field.
The more the technology of face recognition advances, the greater discriminative features …

The advancement in the field of deep neural network (NN) leads practical recognition
systems for biometrics such as face but also increases the threat to privacy such as …

As automated face recognition applications tend towards ubiquity, there is a growing need to
secure the sensitive face data used within these systems. This paper presents a survey of …

The increasing use of multi-biometric authentication has raised concerns about the security
of biometric templates. Many template protection methods based on convolutional neural …

Recently, biometric recognition has become a significant field of research. The concept of
cancelable biometrics (CB) has been introduced to address security concerns related to the …