Content-adaptive steganography by minimizing statistical detectability
Most current steganographic schemes embed the secret payload by minimizing a
heuristically defined distortion. Similarly, their security is evaluated empirically using …
heuristically defined distortion. Similarly, their security is evaluated empirically using …
Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatch
Since the BOSS competition, in 2010, most steganalysis approaches use a learning
methodology involving two steps: feature extraction, such as the Rich Models (RM), for the …
methodology involving two steps: feature extraction, such as the Rich Models (RM), for the …
Is ensemble classifier needed for steganalysis in high-dimensional feature spaces?
The ensemble classifier, based on Fisher Linear Discriminant base learners, was introduced
specifically for steganalysis of digital media, which currently uses high-dimensional feature …
specifically for steganalysis of digital media, which currently uses high-dimensional feature …
Modeling and extending the ensemble classifier for steganalysis of digital images using hypothesis testing theory
R Cogranne, J Fridrich - IEEE Transactions on Information …, 2015 - ieeexplore.ieee.org
The machine learning paradigm currently predominantly used for steganalysis of digital
images works on the principle of fusing the decisions of many weak base learners. In this …
images works on the principle of fusing the decisions of many weak base learners. In this …
Adversarial steganography based on sparse cover enhancement
Abstract CNN (Convolutional Neural Network) steganalyzers achieve enormous
improvements in detecting stego images. However, they are easily deceived by adversarial …
improvements in detecting stego images. However, they are easily deceived by adversarial …
Camera model identification based on the generalized noise model in natural images
TH Thai, F Retraint, R Cogranne - Digital Signal Processing, 2016 - Elsevier
The goal of this paper is to design a statistical test for the camera model identification
problem. The approach is based on the generalized noise model that is developed by …
problem. The approach is based on the generalized noise model that is developed by …
Deep learning in steganography and steganalysis from 2015 to 2018
M Chaumont - arXiv preprint arXiv:1904.01444, 2019 - arxiv.org
For almost 10 years, the detection of a hidden message in an image has been mainly
carried out by the computation of Rich Models (RM), followed by classification using an …
carried out by the computation of Rich Models (RM), followed by classification using an …
On the adversarial robustness of hypothesis testing
In this paper, we investigate the adversarial robustness of hypothesis testing rules. In the
considered model, after a sample is generated, it will be modified by an adversary before …
considered model, after a sample is generated, it will be modified by an adversary before …
Quality optimized medical image information hiding algorithm that employs edge detection and data coding
H Al-Dmour, A Al-Ani - Computer methods and programs in biomedicine, 2016 - Elsevier
Objectives The present work has the goal of developing a secure medical imaging
information system based on a combined steganography and cryptography technique. It …
information system based on a combined steganography and cryptography technique. It …