Improved steganalysis algorithm against motion vector based video steganography

This paper proposes an improved steganalysis algorithm to detect the secret message hidden in the compressed video. As majority of video steganographic algorithms modify motion vectors (MV) in inter-frame encoding to hide data, aliasing effect may be caused in the distribution of the difference between MVs in two adjacent macroblocks. This phenomenon has been observed in detecting the secret data that were added to the MVs in cover video. To exploit the correlations between the neighboring MVs so as to detect the hidden data more efficiently, we consider the joint distribution of the MV differences between one macroblock and the other two macroblocks neighboring to it. The calculated joint probability mass functions are used to distinguish the stego videos from the non-stego ones. The experimental results show that significant improvement in detection accuracy can be made by using the joint distribution of MV differences instead of the statistics calculated from two neighboring MVs as features.