Flaw in SVD-based Watermarking

Lamarche, Luc; Liu, Yan; Zhao, Jiying

doi:10.1109/ccece.2006.277676

Cited by 14 publications

(4 citation statements)

References 2 publications

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“…It is clear from the nature of the algorithm [20] that a simple filtering or noise attack may lead to a great difficulty in the watermark detection process, whereas our proposed watermarking scheme has good robustness against filtering and noise attacks. Furthermore, the scheme [20] suffers from the ambiguity attack [14]. More specifically, in [20] the watermark extraction process is dependent on the watermark information passed by the embedding stage, and is independent of the watermarked signal being tested.…”

Section: Robustness Testmentioning

confidence: 99%

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

Sengupta

Das

2011

Circuits Syst Signal Process

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In this paper, we propose a new robust and blind audio watermarking algorithm based on singular value decomposition and quantization index modulation. The watermark insertion and extraction methods are based on quantization of the norm of singular values of the blocks. Audio quality evaluation tests show high imperceptibility of the watermark in the audio signal. Simulation results demonstrate that this algorithm is robust against signal-processing and stirmark attacks. The false negative error probability under the proposed scheme is close to zero. Moreover, the proposed algorithm has higher data payload and better performance than the other related audio watermarking schemes available in the literature.Keywords Audio watermarking · False negative error (FNE) · Quantization index modulation (QIM) · Singular value decomposition (SVD)

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Section: Robustness Testmentioning

confidence: 99%

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

Sengupta

Das

2011

Circuits Syst Signal Process

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“…In general, the SVD-based scheme extracts the singular values from the host signals and slightly changes some of those values with respect to the watermark bit. It is robust because the singular values are unchanged under common signal processing [27]. However, the balance between inaudibility and robustness for some audio signals needs to be further improved due to the fact that it has never taken the human perception into consideration.…”

Section: Introductionmentioning

confidence: 99%

Audio Watermarking Scheme Based on Singular Spectrum Analysis and Psychoacoustic Model with Self-Synchronization

Karnjana

Unoki

Aimmanee

et al. 2016

Journal of Electrical and Computer Engineering

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This paper proposes a blind, inaudible, and robust audio watermarking scheme based on singular spectrum analysis (SSA) and the psychoacoustic model 1 (ISO/IEC 11172-3). In this work, SSA is used to analyze the host signals and to extract the singular spectra. A watermark is embedded into the host signals by modifying the singular spectra which are in the convex part of the singular spectrum curve so that this part becomes concave. This modification certainly affects the inaudibility and robustness properties of the watermarking scheme. To satisfy both properties, the modified part of the singular spectrum is determined by a novel parameter selection method based on the psychoacoustic model. The test results showed that the proposed scheme achieves not only inaudibility and robustness but also blindness. In addition, this work showed that the extraction process of a variant of the proposed scheme can extract the watermark without assuming to know the frame positions in advance and without embedding additional synchronization code into the audio content.

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“…Other schemes [7], [8], [12], [14], [15], [17]- [20], [22]- [24] do not use the information and are blind [7], [8], [22]- [24] or non-blind [12], [14], [15], [17]- [20]. It should be noted that the robustness of the first category, which employs some information from the watermark, is likely due to false positive detection [10]. The position of modified singular values can be used as a criterion for categorization as well.…”

Section: Introductionmentioning

confidence: 99%

“…SVD-based audio watermarking, originally proposed in 2005 [9], derives from the watermarking technique employed in visual watermarking [10]. It is done by modifying singular values slightly according to some embedding rules.…”

Section: Introductionmentioning

confidence: 99%

Singular-Spectrum Analysis for Digital Audio Watermarking with Automatic Parameterization and Parameter Estimation

Karnjana

Unoki

Aimmanee

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper proposes a blind, inaudible, robust digitalaudio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation.

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Flaw in SVD-based Watermarking

Cited by 14 publications

References 2 publications

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization

Audio Watermarking Scheme Based on Singular Spectrum Analysis and Psychoacoustic Model with Self-Synchronization

Singular-Spectrum Analysis for Digital Audio Watermarking with Automatic Parameterization and Parameter Estimation

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