Abstract
The social networks transcode uploaded videos in a lossy way, which makes most video steganographic methods become unusable. In this paper, a robust video steganographic method is proposed to resist video transcoding on social networking sites. The luminance component of the raw video is selected as the cover and Quantization Index Modulation (QIM) algorithm based on block statistical features is applied to embed secret messages. To make a good tradeoff between the robustness and visual quality, an iteration in the local transcoder is designed to determine the minimum quantization step for each video. Then, a strategy of selecting robust video frames is proposed to further improve the robustness and security. To avoid sharing information beforehand between the sender and the receiver, a steganographic side channel is built for correct message extraction. Experimental results have shown that our proposed method can provide strong robustness against social networks transcoding, the average bit error rate is less than 1%. Meanwhile, our proposed method achieves a satisfactory level of security performance. It's a robust and secure method for covert communication on social networking sites such as YouTube and Vimeo.
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