Optimizing pixel predictors for steganalysis

Steganalysis of embedding in difference of image pixel pairs by neural network

In this paper a steganalysis method is proposed for pixel value differencing method. This steganographic method, which has been immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image is di_erent as compared with a cover image. A number of characteristics are identified in the di...

New techniques for steganography and steganalysis in the pixel domain

Optimizing Non-Local Pixel Predictors for Reversible Data Hiding

This paper presents a two-step clustering and optimizing pixel prediction method for reversible data hiding, which exploits self-similarities and group structural information of non-local image patches. Pixel predictors play an important role for current prediction-error expansion (PEE) based reversible data hiding schemes. Instead of using a fixed or a contentadaptive predictor for each pixel ...

Steganalysis Method Defeating the Modified Pixel-value Differencing Steganography

Pixel-value differencing (PVD) steganography generates step effects or abnormal high fluctuations in PVD histogram. Since steganalysis exploits these artifacts to defeat the PVD steganography, modified PVD (MPVD) steganography preserving the PVD histogram is recently presented. This paper proposes a novel steganalysis method, in which we embed message one more time into the suspicious image to ...

Model-based steganalysis using invariant features

One of the biggest challenges in universal steganalysis is the identification of reliable features that can be used to detect stego images. In this paper, we present a steganalysis method using features calculated from a measure that is invariant for cover images and is altered for stego images. We derive this measure, which is the ratio of any two Fourier coefficients of the distribution of th...