40 citations · 65 across the 7 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.CR2018★ 17 cited
Interpretable Deep Learning under Fire
Xinyang Zhang, Ningfei Wang, Hua Shen +3
Providing explanations for deep neural network (DNN) models is crucial for their use in security-sensitive domains. A plethora of interpretation models have been proposed to help u…
cs.CR2018★ 2 cited
EagleEye: Attack-Agnostic Defense against Adversarial Inputs (Technical Report)
Yujie Ji, Xinyang Zhang, Ting Wang
Deep neural networks (DNNs) are inherently vulnerable to adversarial inputs: such maliciously crafted samples trigger DNNs to misbehave, leading to detrimental consequences for DNN…
cs.CR2018★ 40 cited
Differentially Private Releasing via Deep Generative Model (Technical Report)
Xinyang Zhang, Shouling Ji, Ting Wang
Privacy-preserving releasing of complex data (e.g., image, text, audio) represents a long-standing challenge for the data mining research community. Due to rich semantics of the da…