169 citations · 614 across the 29 of their papers we have counts for
6 papers · 1 filter
Trimming Mobile Applications for Bandwidth-Challenged Networks in Developing Regions
Qinge Xie, Qingyuan Gong, Xinlei He +4
Despite continuous efforts to build and update network infrastructure, mobile devices in developing regions continue to be constrained by limited bandwidth. Unfortunately, this coi…
"How do urban incidents affect traffic speed?" A Deep Graph Convolutional Network for Incident-driven Traffic Speed Prediction
Qinge Xie, Tiancheng Guo, Yang Chen +3
Accurate traffic speed prediction is an important and challenging topic for transportation planning. Previous studies on traffic speed prediction predominately used spatio-temporal…
Piracy Resistant Watermarks for Deep Neural Networks
Huiying Li, Emily Wenger, Shawn Shan +2
As companies continue to invest heavily in larger, more accurate and more robust deep learning models, they are exploring approaches to monetize their models while protecting their…
Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks
Yuanshun Yao, Huiying Li, Haitao Zheng +1
Recent work has proposed the concept of backdoor attacks on deep neural networks (DNNs), where misbehaviors are hidden inside "normal" models, only to be triggered by very specific…
Understanding the Effectiveness of Ultrasonic Microphone Jammer
Yuxin Chen, Huiying Li, Steven Nagels +4
Recent works have explained the principle of using ultrasonic transmissions to jam nearby microphones. These signals are inaudible to nearby users, but leverage "hardware nonlinear…
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
Shawn Shan, Emily Wenger, Bolun Wang +3
Deep neural networks (DNN) are known to be vulnerable to adversarial attacks. Numerous efforts either try to patch weaknesses in trained models, or try to make it difficult or cost…