41 citations · 112 across the 26 of their papers we have counts for
6 papers · 1 filter
Robust and Lossless Fingerprinting of Deep Neural Networks via Pooled Membership Inference
Hanzhou Wu
Deep neural networks (DNNs) have already achieved great success in a lot of application areas and brought profound changes to our society. However, it also raises new security prob…
AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning
Tianxing Zhang, Hanzhou Wu, Xiaofeng Lu +1
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. Th…
Robust and Imperceptible Black-box DNN Watermarking Based on Fourier Perturbation Analysis and Frequency Sensitivity Clustering
Yong Liu, Hanzhou Wu, Xinpeng Zhang
Recently, more and more attention has been focused on the intellectual property protection of deep neural networks (DNNs), promoting DNN watermarking to become a hot research topic…
Verifying Integrity of Deep Ensemble Models by Lossless Black-box Watermarking with Sensitive Samples
Lina Lin, Hanzhou Wu
With the widespread use of deep neural networks (DNNs) in many areas, more and more studies focus on protecting DNN models from intellectual property (IP) infringement. Many existi…
Autoregressive Linguistic Steganography Based on BERT and Consistency Coding
Xiaoyan Zheng, Hanzhou Wu
Linguistic steganography (LS) conceals the presence of communication by embedding secret information into a text. How to generate a high-quality text carrying secret information is…
Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding
Tianyu Yang, Hanzhou Wu, Biao Yi +2
Linguistic steganography (LS) aims to embed secret information into a highly encoded text for covert communication. It can be roughly divided to two main categories, i.e., modifica…