The proposed robust reversible watermarking algorithm addresses the compatibility challenges between robustness and reversibility in existing video watermarking techniques by leveraging scene smoothness for frame grouping videos. Grounded in the H.264 video coding standard, the algorithm first employs traditional robust watermark stitching technology to embed watermark information in the low-frequency coefficient domain of the U channel. Subsequently, it utilizes histogram migration techniques in the high-frequency coefficient domain of the U channel to embed auxiliary information, enabling successful watermark extraction and lossless recovery of the original video content. Experimental results demonstrate the algorithm’s strong imperceptibility, with each embedded frame in the experimental videos achieving a mean peak signal-to-noise ratio of 49.3830 dB and a mean structural similarity of 0.9996. Compared with the three comparison algorithms, the performance of the two experimental indexes is improved by 7.59% and 0.4% on average. At the same time, the proposed algorithm has strong robustness to both offline and online attacks: In the face of offline attacks, the average normalized correlation coefficient between the extracted watermark and the original watermark is 0.9989, and the average bit error rate is 0.0089. In the face of online attacks, the normalized correlation coefficient between the extracted watermark and the original watermark is 0.8840, and the mean bit error rate is 0.2269. Compared with the three comparison algorithms, the performance of the two experimental indexes is improved by 1.27% and 18.16% on average, highlighting the algorithm’s robustness. Furthermore, the algorithm exhibits low computational complexity, with the mean encoding and the mean decoding time differentials during experimental video processing being 3.934 and 2.273 s, respectively, underscoring its practical utility.

Recently proposed steganalysis methods based on the local optimality of motion vector prediction (MVP) indicate that the existing HEVC (high efficiency video coding) motion vector (MV) domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction (AMVP) technology. In order to improve the security of steganography algorithm, this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference (MVD). First, we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features. Then, a distortion function for minimizing embedding distortion is designed, and an algorithm for secret message embedding and extraction in units of inter-frame is proposed. Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods. In addition, the proposed algorithm has excellent performance in visual quality and coding efficiency, and can be applied to practical scenarios of video covert communication.

A novel reversible data hiding algorithm for H.264/AVC videos is proposed. Histogram Shifting (HS) of motion vector values is used efficiently in reversible data hiding to embed data. By designating a specific decoded reference frame, the distortion accumulation effects due to modification of the motion vectors is overcome. All the extracted information can be recovered without loss of the original compressed video carrier. The experimental results show that the proposed algorithm is simple, has higher capacity and invisibility than other existing schemes, and can adjust the relationship between capacity and invisibility according to embedded load.