154 citations · 196 across the 9 of their papers we have counts for
4 papers · 1 filter
SwitchPatch: Physical Adversarial Attack Strategy with Switchable Adversarial Objectives
Hanrui Jiang, Yutong Wu, Shiyi Yao +5
Physical adversarial patch (PAP) attacks attach carefully crafted patches to physical objects to manipulate a deployed model. However, existing PAP attacks suffer from several limi…
Model Supply Chain Poisoning: Backdooring Pre-trained Models via Embedding Indistinguishability
Hao Wang, Shangwei Guo, Jialing He +3
Pre-trained models (PTMs) are widely adopted across various downstream tasks in the machine learning supply chain. Adopting untrustworthy PTMs introduces significant security risks…
Erase and Repair: An Efficient Box-Free Removal Attack on High-Capacity Deep Hiding
Hangcheng Liu, Tao Xiang, Shangwei Guo +3
Deep hiding, embedding images with others using deep neural networks, has demonstrated impressive efficacy in increasing the message capacity and robustness of secret sharing. In t…
PEEL: A Provable Removal Attack on Deep Hiding
Tao Xiang, Hangcheng Liu, Shangwei Guo +1
Deep hiding, embedding images into another using deep neural networks, has shown its great power in increasing the message capacity and robustness. In this paper, we conduct an in-…