Deep learning for steganalysis via convolutional neural networks
Current work on steganalysis for digital images is focused on the construction of complex
handcrafted features. This paper proposes a new paradigm for steganalysis to learn features …
handcrafted features. This paper proposes a new paradigm for steganalysis to learn features …
Random projections of residuals for digital image steganalysis
V Holub, J Fridrich - IEEE Transactions on information forensics …, 2013 - ieeexplore.ieee.org
The traditional way to represent digital images for feature based steganalysis is to compute
a noise residual from the image using a pixel predictor and then form the feature as a …
a noise residual from the image using a pixel predictor and then form the feature as a …
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 …
Investigation on cost assignment in spatial image steganography
Relating the embedding cost in a distortion function to statistical detectability is an open vital
problem in modern steganography. In this paper, we take one step forward by formulating …
problem in modern steganography. In this paper, we take one step forward by formulating …
Adaptive steganalysis against WOW embedding algorithm
WOW (Wavelet Obtained Weights)[5] is one of the advanced steganographic methods in
spatial domain, which can adaptively embed secret message into cover image according to …
spatial domain, which can adaptively embed secret message into cover image according to …
Image steganalysis using a bee colony based feature selection algorithm
FG Mohammadi, MS Abadeh - Engineering Applications of Artificial …, 2014 - Elsevier
Feature selection is one of the most significant phases of pre-analysis processing, which can
influence the performance of steganalysis. In this paper, we have proposed a new feature …
influence the performance of steganalysis. In this paper, we have proposed a new feature …
Adaptive steganalysis based on embedding probabilities of pixels
In modern steganography, embedding modifications are highly concentrated on the textural
regions within an image, as such regions are difficult to model for steganalysis. Previous …
regions within an image, as such regions are difficult to model for steganalysis. Previous …
Adaptive feature selection for image steganalysis based on classification metrics
Y Ma, X Yu, X Luo, D Liu, Y Zhang - Information Sciences, 2023 - Elsevier
Feature selection can remove redundant and useless features, which is an essential way to
improve steganalysis efficiency. However, with the diversity of steganalysis features, feature …
improve steganalysis efficiency. However, with the diversity of steganalysis features, feature …
Steganalysis of HUGO steganography based on parameter recognition of syndrome-trellis-codes
Abstract Highly Undetectable steGO (HUGO steganography) is a well-known image
steganography method proposed in recent years. The security of HUGO steganography is …
steganography method proposed in recent years. The security of HUGO steganography is …
Dataset mismatched steganalysis using subdomain adaptation with guiding feature
The generalization problem in deep learning has always been an important problem to be
solved. In the field of steganalysis, generalization is also an important factor that makes …
solved. In the field of steganalysis, generalization is also an important factor that makes …