Search Results for author: Hanzhou Wu

Found 13 papers, 0 papers with code

JPEG Steganalysis Based on Steganographic Feature Enhancement and Graph Attention Learning

no code implementations5 Feb 2023 Qiyun Liu, Zhiguang Yang, Hanzhou Wu

However, in order to detect whether secret information is hidden within JEPG images, the majority of existing algorithms are designed in conjunction with the popular computer vision related networks, without considering the key characteristics appeared in image steganalysis.

Graph Attention Representation Learning +1

Generative Model Watermarking Based on Human Visual System

no code implementations30 Sep 2022 Li Zhang, Yong liu, Shaoteng Liu, Tianshu Yang, Yexin Wang, Xinpeng Zhang, Hanzhou Wu

Intellectual property protection of deep neural networks is receiving attention from more and more researchers, and the latest research applies model watermarking to generative models for image processing.

Robust and Lossless Fingerprinting of Deep Neural Networks via Pooled Membership Inference

no code implementations9 Sep 2022 Hanzhou Wu

Deep neural networks (DNNs) have already achieved great success in a lot of application areas and brought profound changes to our society.

AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning

no code implementations8 Aug 2022 Tianxing Zhang, Hanzhou Wu, Xiaofeng Lu, Guangling Sun

As a self-supervised learning paradigm, contrastive learning has been widely used to pre-train a powerful encoder as an effective feature extractor for various downstream tasks.

Contrastive Learning Self-Supervised Learning

General Framework for Reversible Data Hiding in Texts Based on Masked Language Modeling

no code implementations21 Jun 2022 Xiaoyan Zheng, Yurun Fang, Hanzhou Wu

To tackle with this problem, in this paper, we propose a general framework to embed secret information into a given cover text, for which the embedded information and the original cover text can be perfectly retrieved from the marked text.

Language Modelling Masked Language Modeling

Verifying Integrity of Deep Ensemble Models by Lossless Black-box Watermarking with Sensitive Samples

no code implementations9 May 2022 Lina Lin, Hanzhou Wu

Though these methods work very well, they were designed for individual DNN models, which cannot be directly applied to deep ensemble models (DEMs) that combine multiple DNN models to make the final decision.

Autoregressive Linguistic Steganography Based on BERT and Consistency Coding

no code implementations26 Mar 2022 Xiaoyan Zheng, Hanzhou Wu

Linguistic steganography (LS) conceals the presence of communication by embedding secret information into a text.

Language Modelling Linguistic steganography

Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding

no code implementations8 Mar 2022 Tianyu Yang, Hanzhou Wu, Biao Yi, Guorui Feng, Xinpeng Zhang

In this paper, we propose a novel LS method to modify a given text by pivoting it between two different languages and embed secret data by applying a GLS-like information encoding strategy.

Language Modelling Linguistic steganography +2

Generating Watermarked Adversarial Texts

no code implementations25 Oct 2021 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 the vulnerability of DNNs, motivating us to find good solutions to improve the robustness of DNN models.

Adversarial Text Text Generation

Graph Representation Learning for Spatial Image Steganalysis

no code implementations3 Oct 2021 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 unavoidably distort the statistical characteristics of the hidden graph features derived from cover images.

Graph Learning Graph Representation Learning +1

Exploiting Language Model for Efficient Linguistic Steganalysis

no code implementations26 Jul 2021 Biao Yi, Hanzhou Wu, Guorui Feng, Xinpeng Zhang

Such kind of difference can be naturally captured by the language model used for generating stego texts.

Language Modelling Steganalysis

Orientation Convolutional Networks for Image Recognition

no code implementations2 Feb 2021 Yalan Qin, Guorui Feng, Hanzhou Wu, Yanli Ren, Xinpeng Zhang

With the propogation of the low-rank structure, the corresponding sparsity for representation of original Gabor filter bank can be significantly promoted.

Watermarking Graph Neural Networks by Random Graphs

no code implementations1 Nov 2020 Xiangyu Zhao, Hanzhou Wu, Xinpeng Zhang

Many learning tasks require us to deal with graph data which contains rich relational information among elements, leading increasing graph neural network (GNN) models to be deployed in industrial products for improving the quality of service.

Model Compression

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