Steganalysis by Subtractive Pixel Adjacency Matrix

An analysis of computational models for accelerating the subtractive pixel adjacency model computation

Article history: Received 20 August 2013 Received in revised form 5 January 2015 Accepted 9 January 2015 Available online 11 March 2015

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...

Optimizing pixel predictors for steganalysis

A standard way to design steganalysis features for digital images is to choose a pixel predictor, use it to compute a noise residual, and then form joint statistics of neighboring residual samples (co-occurrence matrices). This paper proposes a general data-driven approach to optimizing predictors for steganalysis. First, a local pixel predictor is parametrized and then its parameters are deter...

New techniques for steganography and steganalysis in the pixel domain

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 ...