Digital steganography has a long history, starting to be developed in the 90s until now. The
main aspects of early steganography are security, imperceptibility, and payload. Security is …

Social networks are everywhere and currently transmitting very large messages. As a result,
transmitting secret messages in such an environment is worth researching. However, the …

Malware distribution to the victim network is commonly performed through file attachments in
phishing email or from the internet, when the victim interacts with the source of infection. To …

Transmitting images for communication on social networks has become routine, which is
helpful for covert communication. The traditional steganography algorithm is unable to …

Currently, the demand for covert communication in open social networks brings new
opportunities and challenges to existing image steganography technology in terms of …

In recent years, the development of steganalysis based on convolutional neural networks
(CNN) has brought new challenges to the security of image steganography. However, the …

Recent works with the technique of adversarial example have been bringing the possibility
of effectively resisting the machine learning-based steganalyzers. Nevertheless, these …

Although significant progress has been achieved recently in automatic learning of
steganographic cost, the existing methods designed for spatial images cannot be directly …

Existing cover selection methods for steganography mainly focus on embedding distortion of
each image, but ignore the similarity between images. When the cover images are similar, a …

Steganography plays an important role in information hiding. With the development of
steganalysis, traditional steganography faces more detection threat. It is necessary to …