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 [BibTeX] [Marc21]
Are GAN-based Morphs Threatening Face Recognition?
Type of publication: Conference paper
Citation: Sarkar_ICASSP_2022
Publication status: Accepted
Booktitle: International Conference on Acoustics, Speech and Signal Processing
Year: 2022
Month: May
Abstract: Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control. Research in generation of face morphs and their detection is developing rapidly, however very few datasets with morphing attacks and open-source detection toolkits are publicly available. This paper bridges this gap by providing two datasets and the corresponding code for four types of morphing attacks: two that rely on facial landmarks based on OpenCV and FaceMorpher, and two that use StyleGAN 2 to generate synthetic morphs. We also conduct extensive experiments to assess the vulnerability of four state-of-the-art face recognition systems, including FaceNet, VGG-Face, ArcFace, and ISV. Surprisingly, the experiments demonstrate that, although visually more appealing, morphs based on StyleGAN 2 do not pose a significant threat to the state to face recognition systems, as these morphs were outmatched by the simple morphs that are based facial landmarks.
Keywords: Biometrics, Face Recognition, Morphing Attack, StyleGAN 2, Vulnerability Analysis
Projects Idiap
Biometrics Center
Authors Sarkar, Eklavya
Korshunov, Pavel
Colbois, Laurent
Marcel, S├ębastien
Added by: [UNK]
Total mark: 0
Attachments
  • Sarkar_ICASSP_2022.pdf
Notes