LSB matching steganalysis based on patterns of pixel differences and random embedding

This paper presents a novel method for detection of LSB matching steganography in grayscale images. This method is based on the analysis of the differences between neighboring pixels before and after random data embedding. In natural images, there is a strong correlation between adjacent pixels. This correlation is disturbed by LSB matching generating new types of correlations. The presented method generates patterns from these correlations and analyzes their variation when random data are hidden. The experiments performed for two different image databases show that the method yields better classification accuracy compared to prior art for both LSB matching and HUGO steganography. In addition, although the method is designed for the spatial domain, some experiments show its applicability also for detecting JPEG steganography.