An Audio Watermark Designed for Efficient and Robust Resynchronization After Analog Playback

Nadeau, Andrew; Sharma, Gaurav

doi:10.1109/tifs.2017.2661724

Cited by 23 publications

(5 citation statements)

References 23 publications

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“…It is difficult to resist these attacks by considering only the embedding and extraction algorithms. Various strategies for selecting embedding regions have been proposed in the literature, among which RASE [ 36 ] and RFPS [ 37 ] can resist crop and framing errors, A WSOLA-based strategy [ 38 ] can resist playback. These strategies can replace Step 1 in Section 6 to resist the corresponding attacks.…”

Section: Experiments and Discussionmentioning

confidence: 99%

ECSS: High-Embedding-Capacity Audio Watermarking with Diversity Reception

Huang

Guan

et al. 2022

Entropy

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Digital audio watermarking is a promising technology for copyright protection, yet its low embedding capacity remains a challenge for widespread applications. In this paper, the spread-spectrum watermarking algorithm is viewed as a communication channel, and the embedding capacity is analyzed and modeled with information theory. Following this embedding capacity model, we propose the extended-codebook spread-spectrum (ECSS) watermarking algorithm to heighten the embedding capacity. In addition, the diversity reception (DR) mechanism is adopted to optimize the proposed algorithm to obtain both high embedding capacity and strong robustness while the imperceptibility is guaranteed. We experimentally verify the effectiveness of the ECSS algorithm and the DR mechanism, evaluate the performance of the proposed algorithm against common signal processing attacks, and compare the performance with existing high-capacity algorithms. The experiments demonstrate that the proposed algorithm achieves a high embedding capacity with applicable imperceptibility and robustness.

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Section: Experiments and Discussionmentioning

confidence: 99%

ECSS: High-Embedding-Capacity Audio Watermarking with Diversity Reception

Huang

Guan

et al. 2022

Entropy

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“…Conventionally, digital watermarks were extensively used in protecting the ownership of multimedia contents, including images [9,10], videos [11,12], audio [13][14][15], or functional designs [16]. The first effort that propose to use digital watermarking technology in CNNs was a white-box protection by Uchida et al [1], who had successfully embedded watermarks into CNNs without impairing the performance of the host network.…”

Section: Related Workmentioning

confidence: 99%

“…15 show the standard CNN models for CIFAR-10 and CUB-200 used in our experiments on image generation (i.e. DCGAN).…”

mentioning

confidence: 99%

Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack

Ong¹,

Chan²,

Ng³

et al. 2021

Preprint

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Ever since Machine Learning as a Service (MLaaS) emerges as a viable business that utilizes deep learning models to generate lucrative revenue, Intellectual Property Right (IPR) has become a major concern because these deep learning models can easily be replicated, shared, and re-distributed by any unauthorized third parties. To the best of our knowledge, one of the prominent deep learning models -Generative Adversarial Networks (GANs) which has been widely used to create photorealistic image are totally unprotected despite the existence of pioneering IPR protection methodology for Convolutional Neural Networks (CNNs). This paper therefore presents a complete protection framework in both black-box and white-box settings to enforce IPR protection on GANs. Empirically, we show that the proposed method does not compromise the original GANs performance (i.e. image generation, image superresolution, style transfer), and at the same time, it is able to withstand both removal and ambiguity attacks against embedded watermarks.

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“…For example, few audio watermarking systems have been designed to withstand desynchronization between the encoder and decoder [5,6,7,8,9,10]. This robustness could be achieved through using features that are robust to local time-scale variations [5], or deploying a special synchronization mechanism (through time-warping like procedure) at the decoder [8,9]. On the other hand, some earlier works have focused on the reverberation impact while assuming perfect synchronization [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…The relevant work in the literature has treated these two challenges rather separately, and frequently at the cost of less robustness to standard audio processing operations. For example, few audio watermarking systems have been designed to withstand desynchronization between the encoder and decoder [5,6,7,8,9,10]. This robustness could be achieved through using features that are robust to local time-scale variations [5], or deploying a special synchronization mechanism (through time-warping like procedure) at the decoder [8,9].…”

Section: Introductionmentioning

confidence: 99%

Audio Watermarking over the Air with Modulated Self-correlation

Tai

Mansour

2019

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a novel audio watermarking system that is robust to the distortion due to the indoor acoustic propagation channel between the loudspeaker and the receiving microphone. The system utilizes a set of new algorithms that effectively mitigate the impact of room reverberation and interfering sound sources without using dereverberation procedures. The decoder has low-latency and it operates asynchronously, which alleviates the need for explicit synchronization with the encoder. It is also robust to standard audio processing operations in legacy watermarking systems, e.g., compression and volume change. The effectiveness of the system is established with a real-time system under general room conditions.

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An Audio Watermark Designed for Efficient and Robust Resynchronization After Analog Playback

Cited by 23 publications

References 23 publications

ECSS: High-Embedding-Capacity Audio Watermarking with Diversity Reception

ECSS: High-Embedding-Capacity Audio Watermarking with Diversity Reception

Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack

Audio Watermarking over the Air with Modulated Self-correlation

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