Universal spatial feature set for video steganalysis

Xikai Xu, Jing Dong, Tieniu Tan

Abstract: In this paper, we propose a universal spatial feature set for video steganalysis. This feature set comprehensively exploits the correlation of adjacent pixels and can be viewed as a generalized extension of most correlation based features. We also develop a new approach to extract inter-frame features for video steganalysis. Our method can be universally applied to detect different video steganographic algorithms regardless of video format. The experimental results show that it outperforms current correlation based methods.