Sep 10, 2020 · In this paper, we propose a new linguistic steganography based on Variational Auto-Encoder (VAE), which can be called VAE-Stega.
We use the encoder in VAE-Stega to learn the overall statistical distribution characteristics of a large number of normal texts, and then use the decoder in VAE ...
Experimental results show that the proposed model can greatly improve the imperceptibility of the generated steganographic sentences and thus achieves the ...
Aug 25, 2020 · Experimental results show that the proposed model can achieve currently the best performance of text steganalysis and hidden capacity estimation ...
This code belongs to "VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder". Requirements. python 3; tensorflow = 1.12; zhusuan = 0.3.1; gensim ...
RNN-Stega: Linguistic Steganography Based on Recurrent Neural Networks; VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder; KC-Stega ...
VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder. Z Yang, S Zhang,Y Hu, Z Hu, Y Huang. IEEE Transactions on Information Forensics and ...
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The objective of linguistic steganography is to embed additional data in text carriers for covert communication, whereas linguistic steganalysis, ...
A linguistic steganography based on recurrent neural networks, which can automatically generate high-quality text covers on the basis of a secret bitstream ...
Jun 28, 2023 · This paper draws on contrastive learning to design a text steganalysis framework incorporating supervised contrastive loss into the training process.