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) …

Steganography and steganalysis are two interrelated aspects of the field of information
security. Steganography seeks to conceal communications, whereas steganalysis aims to …

Many attempts have been made to hide information in images, where the main challenge is
how to increase the payload capacity without the container image being detected as …

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 …

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 …

Uniform embedding was first introduced in 2012 for non-side-informed JPEG
steganography, and then extended to the side-informed JPEG steganography in 2014. The …

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 …

Locating hidden data in digital images, otherwise called steganalysis, is a process of
identifying the existence of secret messages within digital images. Steganalysis is used to …

Detection of modern JPEG steganographic algorithms has traditionally relied on features
aware of the JPEG phase. In this paper, we port JPEG-phase awareness into the …