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[HTML][HTML] Evolving Generative Adversarial Networks to improve image steganography
Images have been repeatedly used as the perfect environment to hide information through
the use of steganography techniques. Whether messages, documents or even other images …
the use of steganography techniques. Whether messages, documents or even other images …
Image steganography approaches and their detection strategies: A survey
Steganography is the art and science of hidden (or covered) communication. In digital
steganography, the bits of image, video, audio and text files are tweaked to represent the …
steganography, the bits of image, video, audio and text files are tweaked to represent the …
CCNet: CNN model with channel attention and convolutional pooling mechanism for spatial image steganalysis
Image steganalysis based on convolutional neural networks (CNN) has attracted great
attention. However, existing networks lack attention to regional features with complex …
attention. However, existing networks lack attention to regional features with complex …
A robust coverless video steganography based on maximum DC coefficients against video attacks
Coverless steganography has been of great interest in recent years, since it is a technology
that can absolutely resist the detection of steganalysis by not modifying the carriers. Most …
that can absolutely resist the detection of steganalysis by not modifying the carriers. Most …
Adaptive HEVC video steganography with high performance based on attention-net and PU partition modes
S He, D Xu, L Yang, W Liang - IEEE Transactions on Multimedia, 2023 - ieeexplore.ieee.org
With the increasing popularity of digital video, video steganography has become a hot
research topic in the field of covert communication and privacy protection. The existing …
research topic in the field of covert communication and privacy protection. The existing …
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 …
An efficient EEG signal classification technique for Brain–Computer Interface using hybrid Deep Learning
Differently-abled individuals always need support from others for their day-to-day activities.
Brain Computer Interface (BCI) has the potential to help those people in carrying out the …
Brain Computer Interface (BCI) has the potential to help those people in carrying out the …
Print-camera resistant image watermarking with deep noise simulation and constrained learning
In this article, an effective print-camera (PC) resistant image watermarking scheme is
proposed. To achieve watermark robustness, most of existing works try to simulate PC noise …
proposed. To achieve watermark robustness, most of existing works try to simulate PC noise …
Image steganography based on smooth cycle-consistent adversarial learning
Steganography is the process of concealing a secret message in ordinary digital media by
making small modifications that try to preserve cover statistics. In this paper, a novel unified …
making small modifications that try to preserve cover statistics. In this paper, a novel unified …
Digital image steganalysis using entropy driven deep neural network
Context-aware steganography techniques are quite popular due to their robustness.
However, steganography techniques are misused to hide inappropriate information in some …
However, steganography techniques are misused to hide inappropriate information in some …