Video Steganography With Optimized Robust Modulation Paths for Lossy Channels

Jie Gan, Hong Zhang, Zihao Guo, Yun Cao

Abstract: Social networks provide an ideal channel for covert communication due to their one-to-many broadcasting nature and the concealment of communication links. Videos, with their rich content and high embedding capacity, serve as suitable carriers for steganography. However, video transcoding performed by social networks often invalidates traditional steganographic methods. To address this challenge, we propose a novel framework based on optimized robust modulation paths. Specifically, we analyze the influence of modulation types on the robustness of embedding units, introduce a cost assignment method to quantify the embedding impact, and develop an optimization strategy to identify robust modulation paths. Experimental results demonstrate that the proposed method achieves an average bit error rate below 0.5% across mainstream social networks, outperforming state-of-the-art methods in terms of robustness while maintaining sufficient steganographic security.

External IDs:dblp:journals/spl/GanZGC25