A video steganalytic algorithm against motion-vector-based steganography

Steganalysis is the art of detecting the information hidden in the media using steganography. In this paper, a steganalytic method is proposed to detect information hidden in the motion vectors of video bit-streams. Based on the statistical analysis of relative properties, the feature classification technique is adopted to determine the existence of hidden messages. The Support Vector Machine (SVM) is used as the discriminator. The experimental results show that the proposed method can detect the hidden data effectively in motion-vector-based steganography algorithms.