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.
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In this paper, we analyze the video steganography technique, which is used to ensure national security and the confidentiality of the information of governmental agencies and enterprises. Videos may be used to transmit secrets and conduct covert communication. As such, we present an algorithm based on a secret sharing scheme and an Error-Correcting Code (ECC), which combines Grey Relational Analysis (GRA) with a partition mode in video compression standard H.264/AVC. First, we process secret information by secret sharing, and then use an ECC to process the obtained information. Moreover, we choose the Discrete Cosine Transform (DCT) blocks using GRA, and then use rules to hide the pretreated information in DCT coefficients of the video frames. Experimental results indicate that our algorithm has good invisibility, better robustness, good anti-steganalysis ability, and little influence on the bit rate of the video carrier. In addition, the bit error rate is low after attacks such as noise, filtering, or frame loss in the simulation environment.