Audio and Video Matching Zero-Watermarking Algorithm Based on NSCT

Di Fan, Wenxue Sun, Huiyuan Zhao, Wenshuo Kang, Changzhi Lv and Wenjie Lu

Complexity, 2022, vol. 2022, 1-14

Abstract: In the Internet age, information security is threatened anytime and anywhere and the copyright protection of audio and video as well as the need for matching detection is increasingly strong. In view of this need, this paper proposes a zero-watermarking algorithm for audio and video matching based on NSCT. The algorithm uses NSCT, DCT, SVD, and Schur decomposition to extract video features and audio features and generates zero-watermark stream through synthesis, which is stored in a third-party organization for detection and identification. The detection algorithm can obtain zero watermark from the audio and video to be tested and judge and locate tampering by comparing with the zero watermark of the third party. From the experimental results, this algorithm can not only detect whether the audio and video are mismatched due to tampering attacks but also locate the mismatched audio and video segments and protect the copyright.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3445583

DOI: 10.1155/2022/3445583

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