The proliferation of video sharing on social networks has created a novel avenue for covert communication. Since most social networking channels are lossy, researchers have devoted efforts to robust video steganography to establish covert communication on social networks. Although there are various methods available, they often overlook the differences between frames in a video and are designed for a single frame. In this paper, we explore the general process of video recompression and present the frame quantization step (FQS) and interframe mutual information (IFMI) to measure the frame difference in the process of video recompression. Based on the two proposed metrics, we design a heuristic frame selection strategy and then propose a new robust video steganographic method in the DWT-SVD domain. Extensive experiments demonstrate that heuristic frame selection can effectively improve the robustness and reduce the computational complexity of video steganography. Our proposed method provides better robustness and higher efficiency than existing methods for building reliable covert communication on social networks, such as YouTube and Vimeo.

中文翻译：

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探索帧差异以增强社交网络上视频隐写术的鲁棒性

社交网络上视频共享的激增为秘密交流创造了一种新的途径。由于大多数社交网络渠道都是有损的，因此研究人员致力于开发强大的视频隐写术，以在社交网络上建立秘密通信。尽管有多种方法可用，但它们常常忽略视频中帧之间的差异，并且是针对单帧设计的。在本文中，我们探讨了视频再压缩的一般过程，并提出了帧量化步长（FQS）和帧间互信息（IFMI）来测量视频再压缩过程中的帧差异。基于这两个提出的指标，我们设计了一种启发式帧选择策略，然后在 DWT-SVD 领域提出了一种新的鲁棒视频隐写方法。大量实验表明，启发式帧选择可以有效提高视频隐写术的鲁棒性并降低计算复杂度。我们提出的方法比在 YouTube 和 Vimeo 等社交网络上建立可靠的隐蔽通信的现有方法提供了更好的鲁棒性和更高的效率。