Steganography is the art of concealing information in a cover media in such a way that the
presence of the information is unknown. Digital image steganography accomplishes the …

With the enhancement of people's security awareness, transmitting secret information
securely has gradually become a demand for the public. Steganography is a technology of …

Steganography detectors built as deep convolutional neural networks have firmly
established themselves as superior to the previous detection paradigm-classifiers based on …

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 …

The security of image steganography is an important basis for evaluating steganography
algorithms. Steganography has recently made great progress in the long-term confrontation …

Generative adversarial network has shown to effectively generate artificial samples
indiscernible from their real counterparts with a united framework of two subnetworks …

Automatic cost learning for steganography based on deep neural networks is receiving
increasing attention. Steganographic methods under such a framework have been shown to …

Steganographic schemes are commonly designed in a way to preserve image statistics or
steganalytic features. Since most of the state-of-the-art steganalytic methods employ a …

Many forensic techniques have recently been developed to determine whether an image
has undergone a specific manipulation operation. When multiple consecutive operations are …

Nowadays, there are plenty of works introducing convolutional neural networks (CNNs) to
the steganalysis and exceeding conventional steganalysis algorithms. These works have …