## 2 Related Works
This standard has a high ability to compress a video segment with a high compression ratio. Thus, it has been widely used in network transmissions. In [18], a new data-hiding scheme based on H.264 was presented. In the proposed scheme, confidential data is hidden by modifying the sign flag of trailing ones and the levels' words in the context-adaptive variable length coding (CAVLC), which is used in the entropy coding of the H.264 technique. A different method based on H.264 is introduced in [19]. This approach conceals secret data within the high-frequency coefficients (trailing ones) of CAVLC coding. Its main advantage lies in its low computational complexity compared to other H.264/AVC-based hiding techniques, making it suitable for real-time implementation. However, this method is not designed for high hiding capacity, as it only embeds 250 bits in a 352 \(\times\) 288 video with 30 frames. The third category consists of raw video methods. These methods aim to leverage the 3D nature of videos by using the time dimension \(t\) for embedding. This extra dimension provides additional properties like motion vectors and motion components [9]. In [20], an adaptive steganography scheme embeds data in a compressed video stream by utilizing the temporal and spatial features of the host video along with the concept of the human visual system. A different hiding scheme utilizing discrete wavelet transform (DWT) and discrete cosine transform (DCT) is introduced in [21]. This method employs a multiple object tracking (MOT) algorithm and error-correcting codes for the embedding process. Initially, the \"Hamming and Bose\" algorithm and the \"Chaudhuri and Hocquenghem\" algorithm are used to encode the secret data. Next, the motion-based MOT algorithm is applied to the host video to identify the areas of interest in moving objects. Finally, the secret message is embedded into the DWT and DCT coefficients of all motion regions in the video, based on the foreground mask. This scheme can embed a secret message that occupies 3.40% of the host video, with a carrier quality of 49.0 dB. In [22], a robust video watermarking method is introduced to embed a watermark image into digital video frames using the variable-temporal length 3D-DCT technique. This approach involves selecting a series of consecutive 8 \(\times\) 8 blocks and applying the 3D-DCT to these blocks. The embedding process occurs in the mid-range coefficients of the individual blocks. This paper introduces a novel video steganography technique that integrates both temporal and spatial redundancy by utilizing the Octree segmentation technique, a spatiotemporal segmentation algorithm. The Octree segmentation technique divides a 3D signal into smaller homogeneous 3D segments. The proposed method applies the 3D-DCT to each homogeneous 3D segment. The energy of each homogeneous 3D segment is concentrated in a few significant frequency components, allowing a considerable amount of insignificant frequency components to be safely replaced with a scaled version of the secret data. As a result, this steganography technique effectively addresses the capacity-imperceptibility trade-off, enabling the hiding of a substantial number of secret bits while preserving the quality of the carrier signal.