Steganalysis of LSB using energy function

Abstract

This paper introduces an approach to estimate energy of pixel associated with its neighbors. We define an energy function of a pixel which replaces the pixel value by mean or median value of its neighborhood. The correlations inherent in a cover signal can be used for steganalysis, i.e, detection of presence of hidden data. Because of the interpixel dependencies exhibited by natural images this function was able to differentiate between cover and stego image. Energy function was modeled using Gibbs distribution even though pixels in an image have the property of Markov Random Field. Our method is trained to specific embedding techniques and has been tested on different textured images and is shown to provide satisfactory result in classifying cover and stego using energy distribution.