6 papers
LSSD: a Controlled Large JPEG Image Database for Deep-Learning-based Steganalysis "into the Wild"
Hugo Ruiz, Mehdi Yedroudj, Marc Chaumont +2
For many years, the image databases used in steganalysis have been relatively small, i.e. about ten thousand images. This limits the diversity of images and thus prevents large-sca…
Analysis of the Scalability of a Deep-Learning Network for Steganography "Into the Wild"
Hugo Ruiz, Marc Chaumont, Mehdi Yedroudj +3
Since the emergence of deep learning and its adoption in steganalysis fields, most of the reference articles kept using small to medium size CNN, and learn them on relatively small…
Steganography using a 3 player game
Mehdi Yedroudj, Frédéric Comby, Marc Chaumont
Image steganography aims to securely embed secret information into cover images. Until now, adaptive embedding algorithms such as S-UNIWARD or Mi-POD, are among the most secure and…
A CNN adapted to time series for the classification of Supernovae
Anthony Brunel, Johanna Pasquet, Jérôme Pasquet +4
Cosmologists are facing the problem of the analysis of a huge quantity of data when observing the sky. The methods used in cosmology are, for the most of them, relying on astrophys…
Yedrouj-Net: An efficient CNN for spatial steganalysis
Mehdi Yedroudj, Frederic Comby, Marc Chaumont
For about 10 years, detecting the presence of a secret message hidden in an image was performed with an Ensemble Classifier trained with Rich features. In recent years, studies suc…
How to augment a small learning set for improving the performances of a CNN-based steganalyzer?
Mehdi Yedroudj, Marc Chaumont, Frédéric Comby
Deep learning and convolutional neural networks (CNN) have been intensively used in many image processing topics during last years. As far as steganalysis is concerned, the use of…