Biometric systems have made tremendous progress over the past decade, thanks to the availability of copious data and computational resources and advances in deep learning methods. As we witness the widespread adoption of these systems, many privacy and security challenges now come to the fore. Biometric systems are capable of deeply analyzing and extracting hidden information that leads to learning specific human attributes. Consequently, the combination of those attributes can reveal one's identity along with personal information merely from their processed biometric samples. The aim of this tutorial is to raise awareness among the biometric community about the alarming urgency of protecting biometric information from the risks its processing presents when it is conducted in an unprotected manner.

This tutorial aims to provide a comprehensive introduction to privacy and security concerns in biometric systems (especially attacks on templates), through the results of existing studies and attacks. Then, it will discuss strategies to mitigate the concerns w.r.t. the different trade-offs to achieve an optimal equilibrium between efficiency, accuracy, security, and privacy. In addition, it will reflect on those solutions, identify gaps in current research, and motivate further research in those directions. Finally, through tangible examples, we provide a hands-on session that concretizes the biometric concepts and challenges discussed in the tutorial. We will also summarize potential research directions for enhancing the security and privacy of biometric systems.