Deep learning for steganalysis of diverse data types: A review of methods, taxonomy, challenges and future directions
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
security. Steganography seeks to conceal communications, whereas steganalysis aims to …
Deep learning applied to steganalysis of digital images: A systematic review
Steganography consists of hiding messages inside some object known as a carrier in order
to establish a covert communication channel so that the act of communication itself goes …
to establish a covert communication channel so that the act of communication itself goes …
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 …
Self-adversarial training incorporating forgery attention for image forgery localization
Image editing techniques enable people to modify the content of an image without leaving
visual traces and thus may cause serious security risks. Hence the detection and localization …
visual traces and thus may cause serious security risks. Hence the detection and localization …
ImageNet pre-trained CNNs for JPEG steganalysis
In this paper, we investigate pre-trained computer-vision deep architectures, such as the
EfficientNet, MixNet, and ResNet for steganalysis. These models pre-trained on ImageNet …
EfficientNet, MixNet, and ResNet for steganalysis. These models pre-trained on ImageNet …
Improving EfficientNet for JPEG steganalysis
In this paper, we study the EfficientNet family pre-trained on ImageNet when used for
steganalysis using transfer learning. We show that certain" surgical modifications" aimed at …
steganalysis using transfer learning. We show that certain" surgical modifications" aimed at …
Reload: Using reinforcement learning to optimize asymmetric distortion for additive steganography
Recently, the success of non-additive steganography has demonstrated that asymmetric
distortion can remarkably improve security performance compared with symmetric cost …
distortion can remarkably improve security performance compared with symmetric cost …
Deep learning for diverse data types steganalysis: A review
Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis is aimed …
security. Steganography seeks to conceal communications, whereas steganalysis is aimed …
PulseEdit: Editing physiological signals in facial videos for privacy protection
Recent studies have shown that physiological signals such as heart beat and breathing can
be remotely captured from human faces using a regular color camera under ambient light …
be remotely captured from human faces using a regular color camera under ambient light …
Breaking ALASKA: Color separation for steganalysis in JPEG domain
This paper describes the architecture and training of detectors developed for the ALASKA
steganalysis challenge. For each quality factor in the range 60-98, several multi-class tile …
steganalysis challenge. For each quality factor in the range 60-98, several multi-class tile …