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Among steganalysis techniques, detection against motion vector (MV)domain-based video steganography in High Efficiency Video Coding (HEVC)standard remains a hot and challenging issue. For the purpose of improving thedetection performance, this paper proposes a steganalysis feature based on theoptimality of predicted MVs with a dimension of one. Firstly, we point out thatthe motion vector prediction (MVP) of the prediction unit (PU) encoded usingthe Advanced Motion Vector Prediction (AMVP) technique satisfies the localoptimality in the cover video. Secondly, we analyze that in HEVC video, messageembedding either using MVP index or motion vector differences (MVD) may destroythe above optimality of MVP. And then, we define the optimal rate of MVP inHEVC video as a steganalysis feature. Finally, we conduct steganalysisdetection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-of-the-art steganalysismethods. The experimental results show that the proposed optimal rate of MVPfor all cover videos is 100\%, while the optimal rate of MVP for all stegovideos is less than 100\%. Therefore, the proposed steganography scheme canaccurately distinguish between cover videos and stego videos, and it isefficiently applied to practical scenarios with no model training and lowcomputational complexity.

A One-dimensional HEVC video steganalysis method using the Optimality of Predicted Motion Vectors