Steganalysis Using Fractal Block Codes and AP Clustering in Grayscale Images

摘要

This paper presents a universal scheme (also called blind scheme) based on fractal compression and affinity propagation (AP) clustering to distinguish stego-images from cover grayscale images, which is a very challenging problem in steganalysis. Since fractal codes represent the "self-similarity" features of natural images, we adopt the statistical moment of fractal codes as the image features. We first build an image set to store the statistical features of natural images with and without hidden messages, and then apply the AP clustering technique to group this set. The experimental result shows that the proposed scheme performs better than Fridrich's traditional method.