Image steganalysis with binary similarity measures

We present a novel technique for steganalysis of images that have been subjected to embedding by steganographic algorithms. The seventh and eighth bit planes in an image are used for the computation of several binary similarity measures. The basic idea is that the correlation between the bit planes as well as the binary texture characteristics within the bit planes will differ between a stego image and a cover image. These telltale marks are used to construct a classifier that can distinguish between stego and cover images. We also provide experimental results using some of the latest steganographic algorithms. The proposed scheme is found to have complementary performance vis-à-vis Farid's scheme in that they outperform each other in alternate embedding techniques.