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M-Sequences and Sliding Window Based Audio Watermarking Robust Against Large-Scale Cropping Attacks
IEEE Transactions on Information Forensics and Security ( IF 6.8 ) Pub Date : 2023-01-12 , DOI: 10.1109/tifs.2023.3236456
Guofu Zhang 1 , Lulu Zheng 1 , Zhaopin Su 1 , Yifei Zeng 1 , Guoquan Wang 1
Affiliation  

Large-scale cropping (LSC) is one of the mostly-used operations in desynchronization attacks and can easily destroy the watermark information by deleting continuous audio slices from the watermarked audio. In this work, we propose a spread spectrum (SS) based audio watermarking scheme to resist against LSC attacks more robustly from both theoretical and empirical perspectives. Specifically, we first perform discrete wavelet transform (DWT), graph-based transform (GBT), and singular value decomposition (SVD) on the host audio signal to produce transform coefficients. Next, we embed the chaotic encrypted watermark into DWT-GBT-SVD coefficients by the SS technique. Then, we combine m-sequences with the encrypted watermark to generate the watermarking key, which can theoretically guarantee the self-restoration of the cropped watermark based on the periodicity of m-sequences. Additionally, we develop an effective sliding window (SW) strategy to extract the fragmentary watermark slices from DWT-GBT-SVD coefficients and restore the integral watermark by the watermarking key. Finally, the proposed audio watermarking scheme, named m-SW-LSC, is compared with the state-of-the-art audio watermarking methods on audio signals with different genres and lengths under various attacks with different ratios. Experimental results demonstrate that our m-SW-LSC has a superior performance in restoring the complete watermark and exhibits significantly high robustness against LSC attacks.

中文翻译:

基于 M 序列和滑动窗口的音频水印对大规模裁剪攻击具有鲁棒性

大规模裁剪(LSC)是去同步攻击中最常用的操作之一,可以通过从带水印的音频中删除连续的音频片段来轻松破坏水印信息。在这项工作中,我们提出了一种基于扩频 (SS) 的音频水印方案,以从理论和实证的角度更有效地抵抗 LSC 攻击。具体来说,我们首先对主机音频信号执行离散小波变换 (DWT)、基于图的变换 (GBT) 和奇异值分解 (SVD) 以生成变换系数。接下来,我们通过 SS 技术将混沌加密水印嵌入到 DWT-GBT-SVD 系数中。然后,我们将 m 序列与加密水印结合起来生成水印密钥,这在理论上可以保证基于m序列周期性的裁剪水印的自恢复。此外,我们开发了一种有效的滑动窗口 (SW) 策略,从 DWT-GBT-SVD 系数中提取碎片水印切片,并通过水印密钥恢复整体水印。最后,将所提出的名为 m-SW-LSC 的音频水印方案与最先进的音频水印方法在不同类型和长度的音频信号上进行了比较,以应对不同比率的各种攻击。实验结果表明,我们的 m-SW-LSC 在恢复完整水印方面具有卓越的性能,并且对 LSC 攻击表现出非常高的鲁棒性。我们开发了一种有效的滑动窗口 (SW) 策略,从 DWT-GBT-SVD 系数中提取碎片水印切片,并通过水印密钥恢复整体水印。最后,将所提出的名为 m-SW-LSC 的音频水印方案与最先进的音频水印方法在不同类型和长度的音频信号上进行了比较,以应对不同比率的各种攻击。实验结果表明,我们的 m-SW-LSC 在恢复完整水印方面具有卓越的性能,并且对 LSC 攻击表现出非常高的鲁棒性。我们开发了一种有效的滑动窗口 (SW) 策略,从 DWT-GBT-SVD 系数中提取碎片水印切片,并通过水印密钥恢复整体水印。最后,将所提出的名为 m-SW-LSC 的音频水印方案与最先进的音频水印方法在不同类型和长度的音频信号上进行了比较,以应对不同比率的各种攻击。实验结果表明,我们的 m-SW-LSC 在恢复完整水印方面具有卓越的性能,并且对 LSC 攻击表现出非常高的鲁棒性。在不同比率的各种攻击下,将不同流派和长度的音频信号与最先进的音频水印方法进行了比较。实验结果表明,我们的 m-SW-LSC 在恢复完整水印方面具有卓越的性能,并且对 LSC 攻击表现出非常高的鲁棒性。在不同比率的各种攻击下,将不同流派和长度的音频信号与最先进的音频水印方法进行了比较。实验结果表明,我们的 m-SW-LSC 在恢复完整水印方面具有卓越的性能,并且对 LSC 攻击表现出非常高的鲁棒性。
更新日期:2023-01-12
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