Steganography is the primary method by which individuals can communicate covertly;
cryptography, on the other hand, fails at this, as it is possible to detect (the presence of) …

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 …

With the coming era of cloud technology, cloud storage is an emerging technology to store
massive digital images, which provides steganography a new fashion to embed secret …

Neural networks have been shown effective in deep steganography for hiding a full image in
another. However, the reason for its success remains not fully clear. Under the existing cover …

In traditional steganographic schemes, RGB three channels payloads are assigned equally
in a true color image. In fact, the security of color image steganography relates not only to …

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 …

Adoption of deep learning in image steganalysis is still in its initial stage. In this paper, we
propose a generic hybrid deep-learning framework for JPEG steganalysis incorporating the …

In this paper,“uniform embedding”(independent of image contents and pixel correlations
while embedding) and “adaptive embedding”(depend on image contents and pixel …

Three-dimensional (3-D) meshes are commonly used to represent virtual surfaces and
volumes. Over the past decade, 3-D meshes have emerged in industrial, medical, and …