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Can GAN Generated Morphs Threaten Face Recognition Systems Equally as Landmark Based Morphs? - Vulnerability and Detection | IEEE Conference Publication | IEEE Xplore
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Can GAN Generated Morphs Threaten Face Recognition Systems Equally as Landmark Based Morphs? - Vulnerability and Detection

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Sushma Venkatesh; Haoyu Zhang; Raghavendra Ramachandra; Kiran Raja; Naser Damer; Christoph Busch
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Abstract:

The primary objective of face morphing is to com-bine face images of different data subjects (e.g. an malicious actor and an accomplice) to generate a face image that can...Show More

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Abstract:

The primary objective of face morphing is to com-bine face images of different data subjects (e.g. an malicious actor and an accomplice) to generate a face image that can be equally verified for both contributing data subjects. In this paper, we propose a new framework for generating face morphs using a newer Generative Adversarial Network (GAN) - StyleGAN. In contrast to earlier works, we generate realistic morphs of both high-quality and high resolution of 1024 × 1024 pixels. With the newly created morphing dataset of 2500 morphed face images, we pose a critical question in this work. (i) Can GAN generated morphs threaten Face Recognition Systems (FRS) equally as Landmark based morphs? Seeking an answer, we benchmark the vulnerability of a Commercial-Off-The-Shelf FRS (COTS) and a deep learning-based FRS (ArcFace). This work also benchmarks the detection approaches for both GAN generated morphs against the landmark based morphs using established Morphing Attack Detection (MAD) schemes.
Published in: 2020 8th International Workshop on Biometrics and Forensics (IWBF)
Date of Conference: 29-30 April 2020
Date Added to IEEE Xplore: 04 June 2020
ISBN Information:
DOI: 10.1109/IWBF49977.2020.9107970
Conference Location: Porto, Portugal
Citations are not available for this document.
Contents

I. Introduction

Due to the widespread deployment of biometric-based identification and verification of individuals, it is essential to observe a biometric characteristic that is reliable, user-friendly and easy to capture. Face biometrics is well suited for this purpose due to its popularity and widespread use for biometric authentication. Moreover we consider the ease of capturing from a distance in a non-intrusive manner and also the recently achieved high recognition accuracy. These properties further enable that face recognition is to be used in various applications that are attributed with high security requirements like border control. However, biometric face recognition systems (FRS) are known to be highly vulnerable to presentation attacks (aka., spoofing attacks) against the capture device [14]. In addition face recognition system can be deceived during the enrolment process by providing manipulated images [4].

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