Progressive Randomization for Steganalysis

In this paper, we describe a new methodology to detect the presence of hidden digital content in the least significant bits (LSB) of images. We introduce the progressive randomization (PR) technique that captures statistical artifacts inserted during the hiding process. Our technique is a progressive application of LSB modifying transformations that receives an image as input, and returns n images that only differ in the LSB from the initial image. Each step of the progressive randomization approach represents a possible content-hiding scenario with increasing size, and increasing LSB entropy. We validate our method with 20,000 real, non-synthetic images. Using only statistical descriptors of LSB occurrences, our method already performs as well or better than comparable techniques in the literature