Compressive Sensing‐Based Audio Semi‐fragile Zero‐Watermarking Algorithm

Tang, Xin; Ma, Zhiliang; Niu, Xinxin; Yang, Yixian

doi:10.1049/cje.2015.07.009

Cited by 12 publications

(6 citation statements)

References 5 publications

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“…This approach is also not viable for images. Likewise, a semi-fragile zero-watermarking approach is proposed in [41] for audio. In comparison with these schemes, the proposed algorithm encrypts patients' identities and embeds their encrypted shares by using fragile zero watermarking reliably, because chaotic randomness prevents unauthorised access to patients' identities.…”

Section: Comparisonsmentioning

confidence: 99%

A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

2022

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The wireless transmission of patients’ particulars and medical data to a specialised centre after an initial screening at a remote health facility may cause potential threats to patients’ data privacy and integrity. Although watermarking can be used to rectify such risks, it should not degrade the medical data, because any change in the data characteristics may lead to a false diagnosis. Hence, zero watermarking can be helpful in these circumstances. At the same time, the transmitted data must create a warning in case of tampering or a malicious attack. Thus, watermarking should be fragile in nature. Consequently, a novel hybrid approach using fragile zero watermarking is proposed in this study. Visual cryptography and chaotic randomness are major components of the proposed algorithm to avoid any breach of information through an illegitimate attempt. The proposed algorithm is evaluated using two datasets: the Digital Database for Screening Mammography and the Mini Mammographic Image Analysis Society database. In addition, a breast cancer detection system using a convolutional neural network is implemented to analyse the diagnosis in case of a malicious attack and after watermark insertion. The experimental results indicate that the proposed algorithm is reliable for privacy protection and data authentication.

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Section: Comparisonsmentioning

confidence: 99%

A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

2022

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“…With the rapid growth and widespread use of digital media content on the Internet, malicious infringement and copyright disputes of digital products are becoming more serious. In recent years, the digital watermarking has been identified as a potential and effective solution to this problem [ 1 , 2 ] . With the watermarking technology, media owners can insert some information into digital products to claim authenticity and ownership.…”

Section: Introductionmentioning

confidence: 99%

Segment‐Adaptive Spread Spectrum Audio Watermarking Using NSGA‐II

Zhang

X³

2021

Chinese J of Electronics

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In the field of robust audio watermarking, how to seek a good trade-off between robustness and imperceptibility is challenging. The existing studies use the same embedding parameter for each part of the audio signal, which ignores that different parts may have different requirements for embedding parameters. In this work, the constraints on imperceptibility are first analysed. Then, we present a segment multi-objective optimization model of the scaling parameter under the constrained Signal-to-noise ratio (SNR) in Spread spectrum (SS) audio watermarking. Additionally, we adopt the Nondominated sorting genetic algorithm II (NSGA-II) to solve the proposed model. Finally, we compare our algorithm (called SS-SNR-NSGA-II) with the existing methods. The experimental results show that the proposed SS-SNR-NSGA-II not only provides flexible choices for different application demands but also achieves more and better trade-offs between imperceptibility and robustness.

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“…The combination of CS and data hiding makes it possible to compress the audio and, at the same time, to hide the watermark. Hua in [1] and Xin in [2] formerly proposed the CS applications in the audio combining with data hiding. In [2], Xin proposed an embedding method on host audio that is semi-fragile zero-watermarking by decomposing the audio in the wavelet domain and applying the CS technique to the audio wavelet coefficients without describing the audio reconstruction to determine the audio quality after the embedding process.…”

Section: Introductionmentioning

confidence: 99%

“…Xin on [2] proposes an insertion method on audio that is semi-fragile by first decomposing audio in the wavelet domain and applying the CS technique to the audio wavelet coefficient. Watermarks inserted in the measurement vector utilize positive and negative signs on the matrix elements.…”

Section: Introductionmentioning

confidence: 99%

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Compressive Sampling with Multiple Bits Spread Spectrum-Based Data Hiding

Budiman¹,

Suksmono²,

Danudirdjo³

2020

Preprint

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We propose a novel data hiding method in an audio host with a compressive sampling technique. An over-complete dictionary represents a group of the watermark. Each row of the dictionary is a Hadamard sequence representing multiple bits of the watermark. Then, the singular values of segment-based host audio in a diagonal matrix multiply by the over-complete dictionary producing a lower size matrix. At the same time, we embed the watermark into the compressed audio. In the detector, we detect the watermark and reconstruct the audio. This proposed method offers not only hiding the information but also compressing the audio host. The application of the proposed method is a broadcast monitoring and biomedical signal recording. We can mark and secure the signal content by hiding the watermark inside the signal while we compress the signal for memory efficiency. We evaluate the performance in terms of payload, compression ratio, audio quality, and watermark quality. The proposed method can hide the data imperceptibly, in range 729-5292 bps with compression ratio 1.47-4.84 and perfect detected watermark.

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Compressive Sensing‐Based Audio Semi‐fragile Zero‐Watermarking Algorithm

Cited by 12 publications

References 5 publications

A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images

Segment‐Adaptive Spread Spectrum Audio Watermarking Using NSGA‐II

Compressive Sampling with Multiple Bits Spread Spectrum-Based Data Hiding

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