RFPS: A Robust Feature Points Detection of Audio Watermarking for Against Desynchronization Attacks in Cyber Security

Lu, Wenhuan; Li, Ling; He, Yuqing; Wei, Jianguo; Xiong, Naixue

doi:10.1109/access.2020.2984283

Cited by 15 publications

(4 citation statements)

References 39 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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“…With the advent of the era of big data, the relationship between big data and multimedia security has become closer; speech plays an important role in our life, such as military, courtrooms, and dissemination of policies [1][2][3]. In some case, speech content contains private information that can be used for judicial expertise.…”

Section: Introductionmentioning

confidence: 99%

GRACED: A Novel Fragile Watermarking for Speech Based on Endpoint Detection

Zhou

Song

Qian

et al. 2022

Security and Communication Networks

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Content authentication and tampering detection of multimedia is a vital application by using digital watermarking. In this paper, we propose a novel fraGile wateRmArking of speeCh based on Endpoint Detection (namely GRACED) to verify the integrity of speech. Firstly, speech signal is framed word by word and each speech frame includes one intact nonsilence word. Subsequently, feature fusion is adopted to generate the fragile watermark which will be embedded into the coefficients of hybrid domain of discrete wavelet transform (DWT) and singular value decomposition (SVD). Finally, the tampering detection is accomplished without using any synchronous code to detect kinds of attacks. Several experiments are executed in order to quantify the performance of the proposed method. Experimental evaluation and comparisons with other schemes demonstrate that the signal-to-noise ratio of the proposed method is high with a favorable imperceptibility. Additionally, the tampering localization of various malicious attacks can be achieved without using synchronous code and the proposed scheme even can determine the attack types.

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“…In modern times, watermarking techniques for a wide range of digital media were utilized as a host cover to hide or embed a piece of information message in such a way that it is imperceptible to a human observer. Usually, the digital media covers can take any form such as images [1][2][3][4][5][6][7], videos [8][9][10][11][12], audio [13][14][15], and DNA sequences [16,17]. Even so the 3D objects are widely available and important, there are a few existing watermarking techniques.…”

Section: Introductionmentioning

confidence: 99%

A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright

Al-Saadi

Ghareeb

Elhadad

2021

Computational Intelligence and Neuroscience

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In this paper, we propose a novel model for 3D object watermarking. The proposed method is based on the properties of the discrete cosine transform (DCT) of the 3D object vertices to embed a secret grayscale image three times. The watermarking process takes place by using the vertices coefficients and the encrypted image pixels. Moreover, the extraction process is totally blind based on the reverse steps of the embedding process to recover the secret grayscale image. Various performance aspects of the method are measured and compared between the original 3D object and the watermarked one using Euclidean distance, Manhattan distance, cosine distance, and correlation distance. The obtained results show that the proposed model provides better performances in terms of execution time and invisibility.

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RFPS: A Robust Feature Points Detection of Audio Watermarking for Against Desynchronization Attacks in Cyber Security

Cited by 15 publications

References 39 publications

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

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

GRACED: A Novel Fragile Watermarking for Speech Based on Endpoint Detection

A Blind Watermarking Model of the 3D Object and the Polygonal Mesh Objects for Securing Copyright

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