Generating Adversarial Examples for Facial Recognition Systems: Limitations and Insights

This study explores the limitations of using autoencoder latent space and principal component analysis to generate adversarial examples that can evade or impersonate facial recognition systems. The proposed methodology was unable to consistently produce high-quality adversarial examples, highlighting the need for more robust techniques and a deeper understanding of the underlying reasons for adversarial vulnerabilities.