66 citations · 108 across the 12 of their papers we have counts for
4 papers · 1 filter
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks
Qingsong Yao, Zecheng He, Yi Lin +3
Deep neural networks (DNNs) for medical images are extremely vulnerable to adversarial examples (AEs), which poses security concerns on clinical decision making. Luckily, medical A…
New Models for Understanding and Reasoning about Speculative Execution Attacks
Zecheng He, Guangyuan Hu, Ruby Lee
Spectre and Meltdown attacks and their variants exploit hardware performance optimization features to cause security breaches. Secret information is accessed and leaked through cov…
Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection
Qingsong Yao, Zecheng He, Hu Han +1
Recent methods in multiple landmark detection based on deep convolutional neural networks (CNNs) reach high accuracy and improve traditional clinical workflow. However, the vulnera…
Smartphone Impostor Detection with Built-in Sensors and Deep Learning
Guangyuan Hu, Zecheng He, Ruby Lee
In this paper, we show that sensor-based impostor detection with deep learning can achieve excellent impostor detection accuracy at lower hardware cost compared to past work on sen…