Detection of T-shirt Presentation Attacks in Face Recognition Systems

TL;DR

This paper evaluates the vulnerability of face recognition systems to T-shirt presentation attacks and proposes a detection method based on spatial consistency checks to identify such attacks.

Contribution

It introduces a new detection approach utilizing spatial consistency analysis to identify T-shirt presentation attacks in face recognition systems.

Findings

T-shirt attacks can compromise face recognition security.

The proposed spatial consistency method reliably detects T-shirt attacks.

Evaluation on the TFPA database demonstrates effectiveness of the detection approach.

Abstract

Face recognition systems are often used for biometric authentication. Nevertheless, it is known that without any protective measures, face recognition systems are vulnerable to presentation attacks. To tackle this security problem, methods for detecting presentation attacks have been developed and shown good detection performance on several benchmark datasets. However, generalising presentation attack detection methods to new and novel types of attacks is an ongoing challenge. In this work, we employ 1,608 T-shirt attacks of the T-shirt Face Presentation Attack (TFPA) database using 100 unique presentation attack instruments together with 152 bona fide presentations. In a comprehensive evaluation, we show that this type of attack can compromise the security of face recognition systems. Furthermore, we propose a detection method based on spatial consistency checks in order to detect said T-shirt attacks. Precisely, state-of-the-art face and person detectors are combined to analyse the spatial positions of detected faces and persons based on which T-shirt attacks can be reliably detected.