The success rate for blind or universal steganalysis lies in the ability to extract the statistical
footprints of image features. Further, the choice of machine learning (ML) algorithm is crucial …

In contrast to steganography, steganalysis is focused on detecting (the main goal of this
research), tracking, extracting, and modifying secret messages transmitted through a covert …

Steganography is to hide secret information in a normal cover, so that the secret information
cannot be detected. With the rapid development of steganography, it's more and more …

Image steganalysis is the task of discovering the hidden message in a multimedia file in
which the steganalysis technique highly depends on the feature elements of the image …

Image steganalysis is to discriminate innocent images and those suspected images with
hidden messages. This task is very challenging for modern adaptive steganography, since …

The spectacular progress of technology related to the information and communication arena
throughout the past epoch made the internet a powerful media for faster communication of …

Although steganalysis has developed rapidly in recent years, it still faces many difficulties
and challenges. Based on the theory of in-depth learning method and image-based general …

This paper proposes a novel feature selection approach to improve the classification
accuracy and reduce the computational complexity in image steganalysis. It is a hybrid filter …

Image steganalysis is the process of detecting the availability of hidden messages in the
cover images. Therefore, it may be considered as a classification problem which categorizes …

To detect the presence of information in a stego image more reliably, a blind JPEG
steganalysis method based on inter-and intra-wavelet subband correlations in the wavelet …