A novel video steganography against local optimality-based steganalysis schemes.

The article focuses on a novel video steganography scheme based on multiple reference frame motion estimation (MRF-ME) designed to preserve the local optimality of modified motion vectors (MVs) in the rate-distortion sense, thereby enhancing security against steganalysis. The proposed method employs a pre-selection stage to identify locally optimal cover MVs, prioritizes embedding in non-reference frames to reduce distortion drift, and uses an efficient search within a fixed window to select modified MVs with minimal rate-distortion cost difference from the original. Experimental results on H.264/AVC videos demonstrate that this scheme outperforms existing MV-based steganographic methods in resisting state-of-the-art steganalysis techniques while maintaining good video compression quality and acceptable computational complexity. The study also highlights ongoing challenges in fully preserving local optimality and suggests future work on integrated distortion functions considering broader impact factors.