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 the
detection performance, this paper proposes a steganalysis feature based on the
optimality of predicted MVs with a dimension of one. Firstly, we point out that
the motion vector prediction (MVP) of the prediction unit (PU) encoded using
the Advanced Motion Vector Prediction (AMVP) technique satisfies the local
optimality in the cover video. Secondly, we analyze that in HEVC video, message
embedding either using MVP index or motion vector differences (MVD) may destroy
the above optimality of MVP. And then, we define the optimal rate of MVP in
HEVC video as a steganalysis feature. Finally, we conduct steganalysis
detection experiments on two general datasets for three popular steganography
methods and compare the performance with four state-of-the-art steganalysis
methods. The experimental results show that the proposed optimal rate of MVP
for all cover videos is 100\%, while the optimal rate of MVP for all stego
videos is less than 100\%. Therefore, the proposed steganography scheme can
accurately distinguish between cover videos and stego videos, and it is
efficiently applied to practical scenarios with no model training and low
computational complexity.

基于高效视频编码中运动矢量优化的隐写分析特征，本文提出一种能够准确识别覆盖视频和隐写视频的隐写方案，并且在无需模型训练和低计算复杂度的实际场景中表现高效。