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

• DOI: 10.48550/arxiv.2308.06464
• Publication Date: 2023-01-01
• Authors: Jun Li; Minqing Zhang; Ke Niu; Yingnan Zhang; Xiaoyuan Yang
• Keywords: Steganalysis; Motion vector

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