1 citations · 2 across the 4 of their papers we have counts for
4 papers
l-Leaks: Membership Inference Attacks with Logits
Shuhao Li, Yajie Wang, Yuanzhang Li +1
Machine Learning (ML) has made unprecedented progress in the past several decades. However, due to the memorability of the training data, ML is susceptible to various attacks, espe…
Improving the Transferability of Adversarial Examples with Restructure Embedded Patches
Huipeng Zhou, Yu-an Tan, Yajie Wang +3
Vision transformers (ViTs) have demonstrated impressive performance in various computer vision tasks. However, the adversarial examples generated by ViTs are challenging to transfe…
Boosting Adversarial Transferability of MLP-Mixer
Haoran Lyu, Yajie Wang, Yu-an Tan +3
The security of models based on new architectures such as MLP-Mixer and ViTs needs to be studied urgently. However, most of the current researches are mainly aimed at the adversari…
Demiguise Attack: Crafting Invisible Semantic Adversarial Perturbations with Perceptual Similarity
Yajie Wang, Shangbo Wu, Wenyi Jiang +3
Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples. Adversarial examples are malicious images with visually imperceptible perturbations. While the…