Detection of ±1 LSB steganography based on the amplitude of histogram local extrema

Recently Zhang et al described an algorithm for the detection of plusmn1 LSB steganography based on the statistics of the amplitudes of local extrema in the greylevel histogram. Experimental results demonstrated performance comparable or superior to other state-of-the-art algorithms. In this paper, we describe improvements to this algorithm to (i) reduce the noise associated with border effects in the histogram, and (ii) extend the analysis to amplitudes of local extrema in the 2D adjacency histogram. Experimental results on a composite database of 7125 images, averaged over a 20-fold cross validation, with classification based on Fisher linear discriminant analysis, demonstrate that the improved algorithm exhibits significantly better performance. The experimetal results are reported in the form of receiver operating characteristic (ROC) curves and summarized by computing the area under the ROC curve (AUC). The new algorithm, using 10 features derived from the ID and 2D histograms, has an AUC value of 0.77 compared to 0.57 for the original algorithm. It also significantly outperforms other state-of-the-art steganalysers.