Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances

TL;DR

This paper reviews iris presentation attack detection methods, discussing attack types, detection techniques, and their integration into real-world iris recognition systems to enhance security against spoofing threats.

Contribution

It provides a comprehensive overview and taxonomy of iris PAD methods, highlighting recent advances and practical integration scenarios.

Findings

Summarizes main types of iris presentation attacks.

Classifies PAD methods into a detailed taxonomy.

Discusses integration strategies for real-world systems.

Abstract

Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real world applications. The deployment of this technology raises questions about the main vulnerabilities and security threats related to these systems. Among these threats presentation attacks stand out as some of the most relevant and studied. Presentation attacks can be defined as presentation of human characteristics or artifacts directly to the capture device of a biometric system trying to interfere its normal operation. In the case of the iris, these attacks include the use of real irises as well as artifacts with different level of sophistication such as photographs or videos. This chapter introduces iris Presentation Attack Detection (PAD) methods that have been developed to reduce the risk posed by presentation attacks. First, we summarise the most popular types of attacks including the main challenges to address. Secondly, we present a taxonomy of Presentation Attack Detection methods as a brief introduction to this very active research area. Finally, we discuss the integration of these methods into Iris Recognition Systems according to the most important scenarios of practical application.