Texture Based Steganalysis of Grayscale Images Using Neural Network

A method of steganalysis of grayscale images based on texture analysis using Spatial Gray Level Dependence Method is presented. A neural network trained with the texture related statistics, extracted from cover images and stego images that are created using one embedding algorithm, is adopted as a classifier. The classifier reliably detects clean images and stego images despite the small data embedding rate of 0.0077. Steganographic tools tested include both spatial and transform domain image hiding techniques. It is worth mentioning that the clean images are effectively distinguished from the stego images on the basis of image texture alone, regardless of the embedding algorithm used.

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