1k citations · 2.7k across the 15 of their papers we have counts for
7 papers · 1 filter
Application-driven Privacy-preserving Data Publishing with Correlated Attributes
Aria Rezaei, Chaowei Xiao, Jie Gao +2
Recent advances in computing have allowed for the possibility to collect large amounts of data on personal activities and private living spaces. To address the privacy concerns of…
Data Poisoning Attack against Unsupervised Node Embedding Methods
Mingjie Sun, Jian Tang, Huichen Li +4
Unsupervised node embedding methods (e.g., DeepWalk, LINE, and node2vec) have attracted growing interests given their simplicity and effectiveness. However, although these methods…
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao, Ruizhi Deng, Bo Li +3
Deep Neural Networks (DNNs) have been widely applied in various recognition tasks. However, recently DNNs have been shown to be vulnerable against adversarial examples, which can m…
Characterizing Audio Adversarial Examples Using Temporal Dependency
Zhuolin Yang, Bo Li, Pin-Yu Chen +1
Recent studies have highlighted adversarial examples as a ubiquitous threat to different neural network models and many downstream applications. Nonetheless, as unique data propert…
Physical Adversarial Examples for Object Detectors
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes +6
Deep neural networks (DNNs) are vulnerable to adversarial examples-maliciously crafted inputs that cause DNNs to make incorrect predictions. Recent work has shown that these attack…
Spatially Transformed Adversarial Examples
Chaowei Xiao, Jun-Yan Zhu, Bo Li +3
Recent studies show that widely used deep neural networks (DNNs) are vulnerable to carefully crafted adversarial examples. Many advanced algorithms have been proposed to generate a…