46 citations · 89 across the 5 of their papers we have counts for
5 papers
MACPruning: Dynamic Operation Pruning to Mitigate Side-Channel DNN Model Extraction
Ruyi Ding, Cheng Gongye, Davis Ranney +2
As deep learning gains popularity, edge IoT devices have seen proliferating deployment of pre-trained Deep Neural Network (DNN) models. These DNNs represent valuable intellectual p…
EMShepherd: Detecting Adversarial Samples via Side-channel Leakage
Ruyi Ding, Cheng Gongye, Siyue Wang +2
Deep Neural Networks (DNN) are vulnerable to adversarial perturbations-small changes crafted deliberately on the input to mislead the model for wrong predictions. Adversarial attac…
NNReArch: A Tensor Program Scheduling Framework Against Neural Network Architecture Reverse Engineering
Yukui Luo, Shijin Duan, Cheng Gongye +2
Architecture reverse engineering has become an emerging attack against deep neural network (DNN) implementations. Several prior works have utilized side-channel leakage to recover…
DeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA
Yukui Luo, Cheng Gongye, Yunsi Fei +1
As Field-programmable gate arrays (FPGAs) are widely adopted in clouds to accelerate Deep Neural Networks (DNN), such virtualization environments have posed many new security issue…
Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks
Pu Zhao, Siyue Wang, Cheng Gongye +3
Despite the great achievements of deep neural networks (DNNs), the vulnerability of state-of-the-art DNNs raises security concerns of DNNs in many application domains requiring hig…