# Robustness of Facial Recognition to GAN-based Face-morphing Attacks

arXiv: https://arxiv.org/abs/2012.10548 · HTML: https://mlsanity.com/paper/2012.10548/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Dec 2020.

## Built on by (most cited first, 2 of 2)

- [Quadruplet Loss For Improving the Robustness to Face Morphing Attacks](https://mlsanity.com/paper/2402.14665/) (2024)
- [MorphGuard: Morph Specific Margin Loss for Enhancing Robustness to Face Morphing Attacks](https://mlsanity.com/paper/2505.10497/) (2025)

## Abstract (arXiv)

Face-morphing attacks have been a cause for concern for a number of years. Striving to remain one step ahead of attackers, researchers have proposed many methods of both creating and detecting morphed images. These detection methods, however, have generally proven to be inadequate. In this work we identify two new, GAN-based methods that an attacker may already have in his arsenal. Each method is evaluated against state-of-the-art facial recognition (FR) algorithms and we demonstrate that improvements to the fidelity of FR algorithms do lead to a reduction in the success rate of attacks provided morphed images are considered when setting operational acceptance thresholds.