A novel robust zero-watermarking algorithm for audio based on sparse representation

Xu, Longting; Huang, Daiyu; Guo, Xing Mei; Rao, Wei; Ji, Yunyun; Li, Ruoyi; Lu, Xiaochen

doi:10.23919/jcc.2021.08.017

Cited by 3 publications

(4 citation statements)

References 33 publications

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“…From the experimental results, we can find that the NC values in our scheme can reach more than 99% when resisting common attacks. So the robustness of proposed scheme and above two schemes [15,16] is comparable.…”

Section: Introductionmentioning

confidence: 83%

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A robust zero-watermarking scheme based on non-negative matrix factorization for audio protection

Guo

Huang

2022

PLoS ONE

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The copyright problem of digital products is becoming more and more prominent. In this case, digital watermarking technology has attracted the attention of many experts and scholars in the field of information security. Among the proposed technologies, zero-watermarking technology has been favored greatly with its excellent imperceptibility. In this paper, a novel robust audio zero-watermarking scheme is designed by applying non-negative matrix decomposition algorithm to zero-watermarking technology. Firstly, the proposed scheme divides the input audio signal into fixed frames, then applies fast Fourier transform(FFT) and non-negative matrix factorization(NMF) algorithm to extract the feature vector of the original audio signal. Finally, XOR the feature vector and the digital watermark sequence to achieve the embedding of zero-watermarking. The experimental results show that the proposed scheme performs more effectively in resisting common and frame-desynchronization attacks than the existing zero-watermarking schemes.

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Section: Introductionmentioning

confidence: 83%

“…The various other attacks are not considered. L.Xu et al [15] propose an audio zero-watermarking method based on sparse representation, the OMP algorithm and K-SVD algorithm are adopted. After that, authors propose a novel zero-watermarking technique based on the GFT [16].…”

Section: Introductionmentioning

confidence: 99%

A robust zero-watermarking scheme based on non-negative matrix factorization for audio protection

Guo

Huang

2022

PLoS ONE

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“…The specific attack types include the following several ways: Table 3 presents the BER and NC values of watermarks extracted by the proposed and related zero-watermarking schemes when resisting desynchronization attacks with 64×64 watermark images. Meanwhile, Figures 4-8, respectively, exhibit the 64×64 watermark images extracted by the proposed scheme, DCT-DWT-SVD scheme, K-SVD scheme [9], GFT-K-means scheme [10] and NMF scheme [14] against four types of desynchronization attacks. According to Table 3, the proposed scheme performs well against all four attack types, especially against TSM attacks, which is better than the other three schemes.…”

Section: Robust Performance Analysis Against Desynchronization Attacksmentioning

confidence: 99%

A zero‐watermarking technique based on i‐vector model for audio copyright protection

Xu,

He,

Guo

2023

Electronics Letters

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Audio zero‐watermarking is a promising technology for audio copyright protection. It does not modify the content of the original carrier and has good imperceptibility. Considering that i‐vector model can map audio signals of different lengths into a vector space of fixed length, which has good robustness against desynchronization attacks, a robust audio zero‐watermarking technique based on i‐vector model is proposed here. The proposed scheme extracts the i‐vector of the input signal to identify its inherent stability features and then generates a key by XOR operation on the watermark and encoded feature sequences. Experimental results show that this scheme can effectively resist common attacks and desynchronization attacks.

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“…Many small-amplitude coefficients are created to use regularity in the input signals to produce sparse representations (Mohanarathinam et al, 2020). In time-frequency dictionaries, audio signals such as musical recordings have a complex geometric regularity (Xu et al, 2021). It is possible to insert watermark data into a digital image, which can be extracted or identified in the watermarked image (Niu et al, 2020).…”

Section: Introduction Of Digital Watermarking In Music Multimediamentioning

confidence: 99%

Copyright Protection of Music Multimedia Works Fused With Digital Audio Watermarking Algorithm

Huang

2023

International Journal of Grid and High Performance Computing

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Copyright law is important in the media sector since an original creative work owner has the exclusive right to consent, publish, broadcast, and even translate or modify their work. A growing number of digital copyright issues can be found behind the widespread use of multimedia technologies. Improvements must be made right away to the copyright infringement prevention approach using digital watermarking. Zero-watermarking has lately gained popularity as one of the alternatives being considered. A novel sparse representation persistent-based digital audio watermarking algorithm (SRP-DAWA) has been presented to increase zero resilience. Using the improved singular value decomposition (iSVD) technique, an optimum over-complete dictionary can be generated from the background audio signal in the suggested method. Using the orthogonal matching pursuit (OMP) method, the sparse coefficient of a fragmented sample data is calculated, and the corresponding sparse matrix is generated.

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A novel robust zero-watermarking algorithm for audio based on sparse representation

Cited by 3 publications

References 33 publications

A robust zero-watermarking scheme based on non-negative matrix factorization for audio protection

A robust zero-watermarking scheme based on non-negative matrix factorization for audio protection

A zero‐watermarking technique based on i‐vector model for audio copyright protection

Copyright Protection of Music Multimedia Works Fused With Digital Audio Watermarking Algorithm

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