Adversarial Attacks and Identity Leakage in De-Identification Systems: An Empirical Study

arXiv:2609.27022 · cs.CV · Submitted 2026-09-22 · Read on arXiv

cs.CV

Submitted: 2026-09-22

Updated: 2026-09-22

Code: https://github.com/ddkang/advex-uar

Terminology

• Adversarial Attacks — 38× in this paper · explained in 1 episode
• Adversarial Examples — 32× in this paper · explained in 2 episodes
• Embeddings — 15× in this paper · explained in 2 episodes
• Adversarial Noise — 14× in this paper · explained in 1 episode
• Robustness — 14× in this paper · explained in 5 episodes
• Transferability — 10× in this paper · explained in 4 episodes
• Aggregation — 7× in this paper · explained in 1 episode
• Loss Function — 5× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Knowledge Distillation — 2× in this paper · explained in 11 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adversarial Transferability — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• International Conference on Pattern Recognition — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Winter Conference on Applications of Computer Vision — 1× in this paper

Sources

• CFA-Net: Controllable Face Anonymization Network with Identity Representation Manipulation
• Rethinking Model Ensemble in Transfer-based Adversarial Attacks
• Adversarial Attacks on Neural Network Policies
• Towards Deep Learning Models Resistant to Adversarial Attacks
• Fant\^omas: Understanding Face Anonymization Reversibility
• Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
• OGAN: Disrupting Deepfakes with an Adversarial Attack that Survives Training
• ReFace: Real-time Adversarial Attacks on Face Recognition Systems
• Decoupled Weight Decay Regularization

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