← Search

Bin Chen*

2 accepted papers

2024

A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks

ECCV 2024oral

"Model Inversion (MI) attacks aim to reconstruct privacy-sensitive training data from released models by utilizing output information, raising extensive concerns about the security of Deep Neural Networks (DNNs). Recent advances in generative adversarial networks (GANs) have contributed significantl…

2024

CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks

ECCV 2024poster

"Transferable targeted adversarial attacks aim to mislead models into outputting adversary-specified predictions in black-box scenarios. Recent studies have introduced single-target attacks that train a generator for each target class to generate highly transferable perturbations, resulting in subst…