Deep residual learning for image steganalysis
Image steganalysis is to discriminate innocent images and those suspected images with
hidden messages. This task is very challenging for modern adaptive steganography, since …
hidden messages. This task is very challenging for modern adaptive steganography, since …
A novel convolutional neural network for image steganalysis with shared normalization
Image steganalysis is to discriminate innocent images (cover images) and those suspected
images (stego images) with hidden messages. The task is challenging since modifications to …
images (stego images) with hidden messages. The task is challenging since modifications to …
A Siamese CNN for image steganalysis
W You, H Zhang, X Zhao - IEEE Transactions on Information …, 2020 - ieeexplore.ieee.org
Image steganalysis is a technique for detecting data hidden in images. Recent research has
shown the powerful capabilities of using convolutional neural networks (CNN) for image …
shown the powerful capabilities of using convolutional neural networks (CNN) for image …
Fast and effective global covariance pooling network for image steganalysis
X Deng, B Chen, W Luo, D Luo - Proceedings of the ACM workshop on …, 2019 - dl.acm.org
Recently, deep learning based methods have achieved superior performance compared to
conventional methods based on hand-crafted features in image steganalysis. However …
conventional methods based on hand-crafted features in image steganalysis. However …
Deep residual network for steganalysis of digital images
M Boroumand, M Chen, J Fridrich - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Steganography detectors built as deep convolutional neural networks have firmly
established themselves as superior to the previous detection paradigm-classifiers based on …
established themselves as superior to the previous detection paradigm-classifiers based on …
A novel image steganography method via deep convolutional generative adversarial networks
The security of image steganography is an important basis for evaluating steganography
algorithms. Steganography has recently made great progress in the long-term confrontation …
algorithms. Steganography has recently made great progress in the long-term confrontation …
Deep learning hierarchical representations for image steganalysis
J Ye, J Ni, Y Yi - IEEE Transactions on Information Forensics …, 2017 - ieeexplore.ieee.org
Nowadays, the prevailing detectors of steganographic communication in digital images
mainly consist of three steps, ie, residual computation, feature extraction, and binary …
mainly consist of three steps, ie, residual computation, feature extraction, and binary …
A survey on deep convolutional neural networks for image steganography and steganalysis
Steganalysis & steganography have witnessed immense progress over the past few years
by the advancement of deep convolutional neural networks (DCNN). In this paper, we …
by the advancement of deep convolutional neural networks (DCNN). In this paper, we …
CALPA-NET: Channel-pruning-assisted deep residual network for steganalysis of digital images
Over the past few years, detection performance improvements of deep-learning based
steganalyzers have been usually achieved through structure expansion. However …
steganalyzers have been usually achieved through structure expansion. However …
Channel attention image steganography with generative adversarial networks
J Tan, X Liao, J Liu, Y Cao… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Recently, extensive research has revealed the enormous potential of deep learning in the
application of image steganography. However, some defects still exist in previous studies on …
application of image steganography. However, some defects still exist in previous studies on …