On the Possible Detectability of Image-In-Image Steganography

This paper investigates the detectability of popular imagein-image steganography schemes 1, 2, 3, 4, 5. In this paradigm, the payload is usually an image of the same size as the Cover image, leading to very high embedding rates. We first show that the embedding yields a mixing process that is...

Systematically Deconstructing APVD Steganography and Its Payload with a Unified Deep Learning Paradigm

In the era of digital communication, steganography allows covert embedding of data within media files. Adaptive Pixel Value Differencing APVD is a steganographic method valued for its high embedding capacity and invisibility, posing challenges for traditional steganalysis. This paper proposes a...

Hierarchical Graph Neural Network for Compressed Speech Steganalysis

Steganalysis methods based on deep learning DL often struggle with computational complexity and challenges in generalizing across different datasets. Incorporating a graph neural network GNN into steganalysis schemes enables the leveraging of relational data for improved detection accuracy and...