19 citations · 42 across the 12 of their papers we have counts for
4 papers · 1 filter
MMA-Diffusion: MultiModal Attack on Diffusion Models
Yijun Yang, Ruiyuan Gao, Xiaosen Wang +3
In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential mi…
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
Yijun Yang, Ruiyuan Gao, Yu Li +2
Adversarial examples (AEs) pose severe threats to the applications of deep neural networks (DNNs) to safety-critical domains, e.g., autonomous driving. While there has been a vast…
MixDefense: A Defense-in-Depth Framework for Adversarial Example Detection Based on Statistical and Semantic Analysis
Yijun Yang, Ruiyuan Gao, Yu Li +2
Machine learning with deep neural networks (DNNs) has become one of the foundation techniques in many safety-critical systems, such as autonomous vehicles and medical diagnosis sys…
Privacy for Rescue: A New Testimony Why Privacy is Vulnerable In Deep Models
Ruiyuan Gao, Ming Dun, Hailong Yang +2
The huge computation demand of deep learning models and limited computation resources on the edge devices calls for the cooperation between edge device and cloud service by splitti…