Video steganography based on block structure, which embeds secret information by modifying Coding Unit (CU) block structure of I-frames, is currently a research hotspot. However, the existing algorithms still suffer from the limitation of poor anti-steganalysis, which results from significantly disrupting the original CU block structure after embedding secret information. To overcome this limitation, this paper proposes a video steganography algorithm based on multiple CU size and block structure distortion. Our algorithm introduces three key innovations: 1) a CU Block Structure Stability Metric (CBSSM) based on CU block structure restoration phenomenon to reveal the reasons for the insufficient anti-steganalysis performance of current algorithms. 2) a novel mapping rule based on multiple CU size to reduce block structure change and enhance embedding capacity. 3) a three-level distortion function based on block structure to better guide the secret information embedding. This triple strategy ensures that the secret information embedding minimizes disruption to the original CU block structure while concealing it primarily in areas where block structure changes occur after recompression, ultimately enhancing the algorithm's anti-steganalysis. Comprehensive experimental results highlight the crucial role of the proposed CBSSM in evaluating anti-steganalysis performance even at a low embedding rate. Meanwhile, compared to State-of-the-Art video steganography algorithms based on block structure, our proposed steganography algorithm exhibits greater anti-steganalysis, as well as further improving visual quality, bitrate increase ratio and embedding capacity.

翻译：基于块结构的视频隐写术通过修改I帧的编码单元（CU）块结构嵌入秘密信息，目前是研究热点。然而，现有算法仍受抗隐写分析能力较差的限制，这是由于嵌入秘密信息后显著破坏了原始CU块结构。为克服这一局限，本文提出一种基于多重CU尺寸与块结构失真的视频隐写算法。该算法引入三项关键创新：1) 基于CU块结构恢复现象的CU块结构稳定性度量（CBSSM），揭示当前算法抗隐写分析性能不足的原因；2) 基于多重CU尺寸的新型映射规则，以减少块结构变化并提升嵌入容量；3) 基于块结构的三级失真函数，更有效地指导秘密信息嵌入。三重策略确保秘密信息嵌入在最小化对原始CU块结构干扰的同时，主要将信息隐藏于重压缩后块结构变化的区域，从而增强算法的抗隐写分析能力。全面实验结果表明，即使低嵌入率下，所提出的CBSSM在评估抗隐写分析性能方面也发挥关键作用。同时，与最先进的基于块结构的视频隐写算法相比，本文提出的隐写算法展现出更强的抗隐写分析能力，并在视觉质量、码率增长率与嵌入容量方面实现进一步提升。