Type of Publication

Conference Papers

Date:

4 /

2024

Status

Published

DOI:

10.1109/IWBF62628.2024.10593860

Quadruplet Loss For Improving the Robustness to Face Morphing Attacks

Featured in:

International Workshop on Biometrics and Forensics

Authors:

Iurii Medvedev and Nuno Gonçalves

Abstract

Recent advancements in deep learning have revolutionized technology and security measures, necessitating robust identification methods. Biometric approaches, leveraging personalized characteristics, offer a promising solution. However, Face Recognition Systems are vulnerable to sophisticated attacks, notably face morphing techniques, enabling the creation of fraudulent documents. In this study, we introduce a novel quadruplet loss function for increasing the robustness of face recognition systems against morphing attacks. Our approach involves specific sampling of face image quadruplets, combined with face morphs, for network training. Experimental results demonstrate the efficiency of our strategy in improving the robustness of face recognition networks against morphing attacks.

Citation
Iurii Medvedev and Nuno Gonçalves, “Quadruplet Loss for Improving the Robustness to Face Morphing Attacks,” 2024 12th International Workshop on Biometrics and Forensics (IWBF), Enschede, Netherlands, 2024, pp. 01-06, DOI: 10.1109/IWBF62628.2024.10593860.

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