[HTML][HTML] Evolving Generative Adversarial Networks to improve image steganography

A Martín, A Hernández, M Alazab, J Jung… - Expert Systems with …, 2023 - Elsevier
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 …

Image steganography approaches and their detection strategies: A survey

MH Kombrink, ZJMH Geradts, M Worring - ACM Computing Surveys, 2024 - dl.acm.org
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 …

CCNet: CNN model with channel attention and convolutional pooling mechanism for spatial image steganalysis

T Fu, L Chen, Z Fu, K Yu, Y Wang - Journal of Visual Communication and …, 2022 - Elsevier
Image steganalysis based on convolutional neural networks (CNN) has attracted great
attention. However, existing networks lack attention to regional features with complex …

A robust coverless video steganography based on maximum DC coefficients against video attacks

L Meng, X Jiang, Z Zhang, Z Li, T Sun - Multimedia Tools and Applications, 2024 - Springer
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 …

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 …

A survey on deep convolutional neural networks for image steganography and steganalysis

I Hussain, J Zeng, X Qin, S Tan - KSII Transactions on Internet and …, 2020 - koreascience.kr
Steganalysis & steganography have witnessed immense progress over the past few years
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

K Medhi, N Hoque, SK Dutta, MI Hussain - Biomedical Signal Processing …, 2022 - Elsevier
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 …

Print-camera resistant image watermarking with deep noise simulation and constrained learning

C Qin, X Li, Z Zhang, F Li, X Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

Image steganography based on smooth cycle-consistent adversarial learning

B Abdollahi, A Harati, AH Taherinia - Journal of Information Security and …, 2023 - Elsevier
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 …

Digital image steganalysis using entropy driven deep neural network

S Agarwal, KH Jung - Journal of Information Security and Applications, 2024 - Elsevier
Context-aware steganography techniques are quite popular due to their robustness.
However, steganography techniques are misused to hide inappropriate information in some …