41 citations · 112 across the 26 of their papers we have counts for
6 papers · 1 filter
Generating Watermarked Adversarial Texts
Mingjie Li, Hanzhou Wu, Xinpeng Zhang
Adversarial example generation has been a hot spot in recent years because it can cause deep neural networks (DNNs) to misclassify the generated adversarial examples, which reveals…
Graph Representation Learning for Spatial Image Steganalysis
Qiyun Liu, Hanzhou Wu
In this paper, we introduce a graph representation learning architecture for spatial image steganalysis, which is motivated by the assumption that steganographic modifications unav…
Exploiting Language Model for Efficient Linguistic Steganalysis
Biao Yi, Hanzhou Wu, Guorui Feng +1
Recent advances in linguistic steganalysis have successively applied CNN, RNN, GNN and other efficient deep models for detecting secret information in generative texts. These metho…
Structural Watermarking to Deep Neural Networks via Network Channel Pruning
Xiangyu Zhao, Yinzhe Yao, Hanzhou Wu +1
In order to protect the intellectual property (IP) of deep neural networks (DNNs), many existing DNN watermarking techniques either embed watermarks directly into the DNN parameter…
Orientation Convolutional Networks for Image Recognition
Yalan Qin, Guorui Feng, Hanzhou Wu +2
Deep Convolutional Neural Networks (DCNNs) are capable of obtaining powerful image representations, which have attracted great attentions in image recognition. However, they are li…
Hiding Data Hiding
Hanzhou Wu, Gen Liu, Xinpeng Zhang
Data hiding is the art of hiding secret data into a cover object such as digital image for covert communication. In this paper, we make the first step towards hiding ``data hiding'…