scholarly journals Adaptive and Blind Audio Watermarking Algorithm Based on Chaotic Encryption in Hybrid Domain

Symmetry ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 284 ◽  
Author(s):  
Qiuling Wu ◽  
Meng Wu
Keyword(s):  
Audio Signal ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Chaotic Encryption ◽  
Average Amplitude ◽  
Blind Audio Watermarking ◽  
Hybrid Domain ◽  
Frequency Components ◽  
Special Embedding ◽  
Audio Media

An adaptive and blind audio watermarking algorithm is proposed based on chaotic encryption in discrete cosine transform (DCT) and discrete wavelet transform (DWT) hybrid domain. Since human ears are not sensitive to small changes in the high-frequency components of the audio media, the encrypted watermark can be embedded into the audio signal according to the special embedding rules. The embedding depth of each audio segment is controlled by the overall average amplitude to effectively improve the robustness and imperceptibility. The watermark is encrypted by a chaotic sequence to improve the security of watermark, so only users who hold the correct key can accurately extract the watermark without the original audio signal. Experimental results show that the proposed algorithm has larger capacity, higher imperceptibility, better security, and stronger robustness when combating against signal-processing attacks than the involved audio watermarking algorithms in recent years.

Audio Watermarking Based on Wavelet Transform

2012 ◽  
Vol 229-231 ◽  
pp. 2784-2788 ◽  
Author(s):  
Mahmoud A. Osman ◽  
Nasser H. Ali
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Audio Signal ◽  
Frequency Component ◽  
Binary Image ◽  
Audio Watermarking ◽  
High Frequency Component ◽  
Discrete Wavelet ◽  
Copyright Information

The process of hiding the information like text, binary image, audio etc. into another signal source like image, audio etc. is called watermarking. The approach involved in watermarking the binary image signal in the wavelet domain of the audio signal was implemented using MATLAB. In this paper, we propose a Discrete Wavelet Transform low frequency to high frequency. Besides, the high frequency spectrum is less sensitive to human ear. That is the reason why the high frequency component is usually discarded in the compression process. Therefore, information to be hidden can be embedded into the low frequency component to against the compression attack. The characteristic of this scheme is that the user can not only use the DAW to embed the text file in to the audio but also binary image. In this paper we embeds copyright information into audio files as a proof of their ownership, we propose an effective, robust, and an inaudible audio watermarking algorithm. The effectiveness of the algorithm has been brought by virtue of applying the discrete wavelets transform (DWT) . Experimental results will be presented in this paper to demonstrate the effectiveness of the proposed algorithm.

scholarly journals Frame-synchronous Blind Audio Watermarking for Tamper Proofing and Self-Recovery

2020 ◽  
Vol 5 (1) ◽  
pp. 18-32
Author(s):  
Hwai-Tsu Hu ◽  
Ying-Hsiang Lu
Keyword(s):  
Audio Signal ◽  
Audio Watermarking ◽  
Frame Synchronization ◽  
Content Authentication ◽  
Blind Audio Watermarking ◽  
Synchronization Mechanism ◽  
Related Data ◽  
Perceptual Evaluation ◽  
Reed Solomon Code ◽  
Watermarking Scheme

This paper presents a lifting wavelet transform (LWT)-based blind audio watermarking scheme designed for tampering detection and self-recovery. Following 3-level LWT decomposition of a host audio, the coefficients in selected subbands are first partitioned into frames for watermarking. To suit different purposes of the watermarking applications, binary information is packed into two groups: frame-related data are embedded in the approximation subband using rational dither modulation; the source-channel coded bit sequence of the host audio is hidden inside the 2nd and 3rd -detail subbands using 2N-ary adaptive quantization index modulation. The frame-related data consists of a synchronization code used for frame alignment and a composite message gathered from four adjacent frames for content authentication. To endow the proposed watermarking scheme with a self-recovering capability, we resort to hashing comparison to identify tampered frames and adopt a Reed–Solomon code to correct symbol errors. The experiment results indicate that the proposed watermarking scheme can accurately locate and recover the tampered regions of the audio signal. The incorporation of the frame synchronization mechanism enables the proposed scheme to resist against cropping and replacement attacks, all of which were unsolvable by previous watermarking schemes. Furthermore, as revealed by the perceptual evaluation of audio quality measures, the quality degradation caused by watermark embedding is merely minor. With all the aforementioned merits, the proposed scheme can find various applications for ownership protection and content authentication.

A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform

2013 ◽  
Vol 93 (4) ◽  
pp. 913-922 ◽  
Author(s):  
Xinkai Wang ◽  
Pengjun Wang ◽  
Peng Zhang ◽  
Shuzheng Xu ◽  
Huazhong Yang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Blind Audio Watermarking ◽  
Norm Space

scholarly journals Intelligent High Payload Audio Watermarking Algorithm Using Colour Image in DWT-SVD Domain

2021 ◽  
Vol 2128 (1) ◽  
pp. 012019
Author(s):  
A R Elshazly ◽  
Mohamed E. Nasr ◽  
M M Fouad ◽  
Fathi E. Abdel-Samie
Keyword(s):  
Chaotic Map ◽  
Audio Signal ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Watermark Image ◽  
Colour Image ◽  
Blind Extraction ◽  
Approximation Coefficients ◽  
Value Decomposition ◽  
High Payload

Abstract Copyright protection and ownership verification of digital audio tracks have become increasingly important to be enabled by digital watermarking techniques. A novel high payload intelligent audio watermarking scheme with RGB color watermark image is proposed in this paper. The color watermark image is encrypted using Arnold chaotic map and passed through an adaptive scaling filter to scale the image to match the required payload. The encoding process is performed on the scaled encrypted version of the watermark image. A portion of the audio signal is used to embed a synchronization code and the other one is decomposed into short frames. These frames are processed with a two-level discrete wavelet transform (DWT), followed by a singular value decomposition (SVD) process on the approximation coefficients. The encoded watermark is inserted into the diagonal matrix using quantization index modulation (QIM). The inverse process of SVD and DWT is applied to obtain the marked audio signal. Blind extraction of the hidden information from the marked audio signal is performed in the reverse order of the embedding process. Experiments show that security, high payload, transparency and imperceptibility of the algorithm are satisfied. The robustness against several kinds of audio signal processing attacks is shown. Performance evaluation tests with SNR, BER, and FSIM are conducted.

scholarly journals Pengaruh Kapasitas Dimensi Citra Watermark terhadap Audio Watermarking dengan Perpaduan Metode DWT (Discrete Wavelet Transform) dan SVD ( Singular Value Decomposition)

2019 ◽  
Vol 6 (2) ◽  
pp. 141
Author(s):  
Togu Novriansyah Turnip ◽  
Jenny Doloksaribu ◽  
Vedtra Purba ◽  
Immanuel Saragih
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Audio Signal ◽  
Singular Value ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Digital Audio ◽  
Copyright Information ◽  
Value Decomposition

<p class="Abstrak">Digital audio <em>watermarking</em> dibutuhkan untuk memberi perlindungan dari pembajakan musik secara ilegal dan pemberian hak cipta/kepemilikan. Penelitian ini menjelaskan perpaduan metode audio <em>watermarking</em> dimana informasi berupa hak cipta disisipkan ke dalam sinyal audio. Perpaduan dari metode DWT (<em>Discrete Wavelet Transfrom</em>) dan SVD (<em>Singular Value Decomposition</em>) digunakan untuk menyisipkan dan mengekstrak <em>watermark</em> dari sinyal audio. Informasi atau watermark tersebut dapat berupa gambar hitam putih (<em>biner</em>) atau huruf-huruf karakter ASCII. Pada penelitian ini sebuah gambar dijadikan sebagai <em>watermark</em> dengan berbagai variasi ukuran piksel seperti 10×10, 30×30, 40×40 dan 50×50 piksel. Hasil dari penyisipan <em>watermark</em> yang berukuran 30×30 piksel menghasilkan <em>imperceptibility</em> yang baik dengan nilai rata-rata diantara 43 sampai dengan 50 dB. Hasil eksperimen yang telah dilakukan juga menunjukkan bahwa kombinasi dari kedua metode tahan (<em>robustness</em>) terhadap beberapa serangan seperti <em>amplify</em>, <em>resampling</em> dan <em>invert</em>.</p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="Judul2"><em>Digital audio watermarking is needed as a protection against online music piracy and </em><em>copyright issues</em><em>. This paper describes an audio watermarking</em><em> combination</em><em> method where </em><em>the </em><em>copyright information is imperceptibly added into the audio signal. The combination of discrete wavelet transform (DWT) and singular value decomposition (SVD) is used to embed and e</em><em>x</em><em>tract the watermark from the audio signal. The copyright information or watermark could be a binary logo or some unique binary pattern</em><em>s</em><em>. In this paper, a watermarked image </em><em>is </em><em>divided into four different capacities of dimension such as 10×10, 30×30</em><em>, </em><em>40×40 and 50×50 pi</em><em>x</em><em>el</em><em>s</em><em>.</em><em> </em><em>The result</em><em>s</em><em> of the watermarked image </em><em>are</em><em> imperceptibly added into the audio signal</em><em> and image with</em><em> 30×30 pixel </em><em>dimension </em><em>ha</em><em>s</em><em> the best mean result ranged from 43 to 50 dB</em><em>.</em><em> The experiment result also show</em><em>s</em><em> that the combination of DWT and SVD is robust against different attacks such as amplify, resampling and invert.</em></p><p class="Judul2"> </p>

scholarly journals Robust and Blind Audio Watermarking Scheme Based on Genetic Algorithm in Dual Transform Domain

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Qiuling Wu ◽  
Aiyan Qu ◽  
Dandan Huang ◽  
Lejun Ma
Keyword(s):  
Genetic Algorithm ◽  
Audio Watermarking ◽  
Transform Domain ◽  
Blind Audio Watermarking ◽  
Performance Requirements ◽  
Payload Capacity ◽  
Minimal Modification ◽  
Watermarking Scheme ◽  
Dual Transform ◽  
Audio Media

In order to protect the copyright of audio media in cyberspace, a robust and blind audio watermarking scheme based on the genetic algorithm (GA) is proposed in a dual transform domain. A formula for calculating the embedding depth is developed, and two embedding depths with different values are used to represent the “1” and “0” states of the binary watermark, respectively. In the extracting process, the embedding depth in each audio fragment will be calculated and compared with the average embedding depth to determine the watermark bit by bit, so this scheme can blindly extract the watermark without the original audio. GA will be applied to optimize the algorithm parameters for meeting the performance requirements in different applications. Besides, the embedding rule is further optimized to enhance the transparency based on the principle of minimal modification to the audio. Experimental results prove that the payload capacity reaches 172.27 bps, the bit error rate (BER) is 0.1% under the premise that its transparency is higher than 25 dB, and its robustness is strong against many attacks. Significantly, this scheme can adaptively select the algorithm parameters to satisfy the specific performance requirements.

scholarly journals High-capacity, transparent and robust blind audio watermarking scheme based DWT and TLBO algorithm

2020 ◽  
Author(s):  
Ali Joudaki ◽  
Marjan Abdeyazdan ◽  
Mohammad Mosleh
Keyword(s):  
Digital Media ◽  
High Capacity ◽  
Audio Signal ◽  
Extraction Process ◽  
Audio Watermarking ◽  
Blind Audio Watermarking ◽  
Tlbo Algorithm ◽  
Payload Capacity ◽  
Low Pass ◽  
Specific Frequency

Abstract Digital watermarking is one of the best solutions again the copyright infringement, duplicates, verifies data and illegal distribution of digital media. Recently, the protection of digital audio signals is one of the attracting and interesting topics for scientific and researchers. In this paper we propose a blind audio watermarking mechanism in which it has high capacity, transparency and resistance simultaneously based on digital wavelet transform (DWT) algorithm. The key principle of this work is that in the DWT procedure, using two filters; break down the original audio signal into several sub-bands and transform them on a specific frequency range. It should be noted that the 8 bits of watermarked signal is selected and transform to the original signal. In order to increase the watermarking resistance, framing the high frequency coefficients of the third level of the wavelet and calculate the frames average and place them in the frame memory prime. Moreover, TLBO algorithm used to determination of embedding and extraction coefficients in order to increase the SNR ratio in the embedding process and decrease the bit error rate (BER) in the extraction process. This method increases the embedding payload capacity while the audio SNR and extracted image BER have good qualify. Moreover, experimental results shown that this method has 13kbs hiding rate,ascendency imperceptibility, good payload capacity and intense robustness when resisting against various attacks such as MP3 compression, re-quantization, low-pass filtering, amplitude scaling, re-sampling, echo addition and noise corruption.

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