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Desynchronization Attacks Resilient Watermarking Method Based on Frequency Singular Value Coefficient Modification

delete2021-01-01
delete23
PRE
AI
赵娟 (Juan Zhao)
T
Tianrui Zong
Y
Yong Xiang *
L
Longxiang Gao
W
Wanlei Zhou
G
Gleb Beliakov
DOI:10.1109/TASLP.2021.3092555delete
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Abstract

Abstract

En 中文
Desynchronization is a very challenging type of attack in audio watermarking. The traditional singular value decomposition (SVD) based audio watermarking methods embed the watermark information by modifying the singular value of individual segment, which have little resistance against desynchronization attacks. In this paper, we propose a novel frequency singular value coefficient (FSVC) feature, which reflects the ratio between the singular values of two consecutive segments and is insensitive to desynchronization attacks, to carry the watermark bits. To our best knowledge, it is the first time that the ratio between singular values is employed for audio watermarking. In the proposed method, the discrete cosine transform (DCT) is performed on two consecutive segments of the host audio signal and SVD is applied to the DCT coefficients of the mid frequency band of each segment to extract the FSVC. Then the watermark bits are embedded by adjusting the values of the FSVC. The watermark embedding procedure is optimized to minimize the perceptual quality degradation and an error buffer is created to enhance the robustness. As a result, the proposed method can achieve a much higher embedding capacity than the existing methods tackling desynchronization attacks. The impact of desynchronization and common signal processing attacks on the proposed watermarking method is mathematically modeled, and the effectiveness of the proposed method against these attacks is theoretically and experimentally validated.
Keywords:
Watermarking
Discrete cosine transforms
Robustness
Synchronization
Time-domain analysis
Time-frequency analysis
Speech processing
Audio watermarking
desynchronization attacks
discrete cosine transform
singular value decomposition

Journal

I
IEEE-ACM Transactions on Audio Speech and Language Processing
IF:
5.1
Papers:
2.6K
Citations:
1.1W

Organization

U
university of technology sydney
Scholars:
1.6W
Papers: 2.0W
Citations: 25
D
Deakin University
Scholars:
2.0W
Papers: 2.1W
Citations: 2.8W