Video Steganalysis Based on the Expanded Markov and Joint Distribution on the Transform Domains Detecting MSU StegoVideo

In this article, we propose a scheme of detecting the information-hiding in videos based on the pairs of condition and joint distributions in the transform domains. Specifically, based on the approach of the Markov-process in JPEG image steganalysis and our previous work, we propose the pairs of condition and joint distribution of the neighbor difference in the transform domains, including discrete cosine transform (DCT) and the discrete wavelet transform (DWT). We apply learning classifiers to the pairs extracted from the video covers and the video steganograms produced by MSU Video Steganograms. Experimental results show that this approach is very successful in detecting the information-hiding in MSU stego video steganograms.