Image steganalysis with binary similarity measures

Abstract

We present a novel technique for steganalysis of images that have been subjected to Least Significant Bit (LSB) type steganographic algorithms. The seventh and eight 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 the binary texture characteristics within the bit planes will differ between a stego-image and a cover-image. These telltale marks can be used to construct a steganalyzer, that is, a multivariate regression scheme to detect the presence of a steganographic message in an image.