基于人工神经网络的数字音频水印算法

提出了一种新的基于神经网络训练学习的数字音频水印算法 ,采用本算法在一段数字音频数据中隐藏了一幅不可感知的二值图像 .通过后向传播算法的神经网络训练出模板信号与嵌入了水印信号的音频之间的关系特征 ,由于神经网络具有学习和自适应的特性 ,通过训练后的神经网络几乎能够完全恢复嵌入到音频中的水印数据 .通过仿真实验结果表明该算法具有较好的鲁棒性和抵抗常用的信号处理方法的处理的能力 ,特别是在水印检测时不需要原始的音频信号 .     

Quality-driven secure audio transmissions in wireless multimedia sensor networks

Many audio applications such as audio surveillance and human acoustic health monitoring require security protections for audio streaming over WSNs. The process of watermarking which embeds small amounts of data (i.e., the watermark) into the original audio is an effective technique to ensure the integrity of received audio data at the receiver in energy-constrained WSNs. However, the selection of positions to embed watermark into audio streams is critical to both received audio quality and watermarking authentication performance in error-prone wireless transmission environments. In this paper we propose an approach that dynamically determines the range of middle sub-band components for embedding the watermark with minimum quality distortions, based on psycho-acoustic models and adaptive sub-band thresholds. In addition, through unequal network resource allocation schemes the proposed approach protects both middle sub-bands and high sub-bands, which include the important audio components. Our theoretical analysis and simulation results demonstrate that the proposed quality-driven energy-efficient watermarking approach for audio transmissions can achieve considerable performance gains in WSNs.     

基于支持向量机(SVM)的数字音频水印

提出了一种新的基于支持向量机（support vector machine,SVM）的数字音频水印算法．主要思想是在宿主音频中嵌入一段模板信息,定义模板信息与宿主音频之间的一种对应关系．将水印的检测问题转化为一个可用SVM处理的二分类问题,利用SVM对先验知识（对应关系）的学习,以达到对未知数字音频水印的正确分类检测．仿真实验结果表明,该数字音频水印具有较强的健壮性和不可感知性,在受到MP3压缩、低通滤波、重采样／量化、噪声干扰等常用信号处理方法的处理后,能正确检测出水印,同时在水印检测时不需要原始音频,实现了水印的盲检测．     

自适应小波域数字音频水印嵌入算法研究

以整型提升小波变换、人类听觉掩蔽特性、数字音频局部邻域特性为基础，提出了一种自适应小波域数字音频水印嵌入算法，该算法具有以下特点：（1）结合人类听觉系统的掩蔽特性，实现了水印嵌入位置的自适应确定；（2）引入了高效的整型提升小波变换；（3）利用数字音频的局部邻域特性，实现了数字水印嵌入深度的智能调节；（4）数字水印信息的提取不需要原始音频信号．对比实验表明：该自适应数字音频水印算法不仅具有较好的透明性，而且对诸如叠加噪声、有损压缩、低通滤波、重新采样、重新量化等攻击均具有较好的鲁棒性（特别是叠加噪声与低通滤波）。     

基于卷积码的盲音频水印算法研究

提出了一种基于提升小波和卷积码的盲音频水印算法。原始音频信号经过提升小波变换后,选取中低频小波系数进行自适应水印嵌入。水印在嵌入前经过卷积编码和交织预处理,以提高水印系统的抗干扰能力。为了增强算法的鲁棒性,水印提取时采用了软判决Viterbi译码。实验结果表明,该水印算法具有较好的性能。     

A New Adaptive Digital Audio Watermarking Based on Support Vector Regression

On the basis of support vector regression (SVR), a new adaptive blind digital audio watermarking algorithm is proposed. This algorithm embeds the template information and watermark signal into the original audio by adaptive quantization according to the local audio correlation and human auditory masking. The procedure of watermark extraction is as follows. First, the corresponding features of template and watermark are extracted from the watermarked audio. Then, the corresponding feature of template is selected as training sample to train SVR and an SVR model is returned. Finally, the actual outputs are predicted according to the corresponding feature of watermark, and the digital watermark is recovered from the watermarked audio by using the well-trained SVR. Experimental results show that our audio watermarking scheme is not only inaudible, but also robust against various common signal processing (such as noise adding, resampling, requantization, and MP3 compression), and also has high practicability. In addition, the algorithm can extract the watermark without the help of the original digital audio signal, and the performance of it is better than other SVM audio watermarking schemes.     

稳健局部特征非下采样小波域数字水印

目的 基于数字水印技术的音乐作品版权保护是学术界的研究热点之一,多数数字音频水印方案仅仅能够对抗简单的常规信号处理,无法有效抵抗破坏性较强的一般性去同步攻击。为此,提出了一种基于稳健局部特征的非下采样小波域数字水印算法。方法 利用非下采样小波域平滑梯度检测算子从载体音频中提取稳定的音频特征点,结合数字音频样本响应确定局部特征音频段,采用量化调制策略将数字水印信号重复嵌入局部特征音频段中。结果 选取4段典型的采样频率为44.1 kHz、量化精度为16 bit、长度为15 s的单声道数字音频信号作为原始载体进行测试,并与经典算法在不可感知性和鲁棒性两方面进行对比。结果表明,本文算法在含水印音频与原始载体音频间的信噪比平均提升了5.7 dB,同时常规攻击和去同步攻击下的平均检测率分别保持在0.925和0.913,高于大多数传统算法,表明了本文算法具有较好的不可感知性。在常规信号处理（MP3压缩、重新量化、重新采样等）和去同步攻击（幅度缩放、随机剪切、音调伸缩、DA/AD转换、抖动等）方面均具有较好的鲁棒性。结论 本文利用描述能力强且性能稳定的平滑梯度刻画局部数字音频性质,提出一种基于平滑梯度的非下采样小波域音频特征点提取方法,有效解决了音频特征点稳定性差且分布极不均匀的缺点,提高了数字音频水印对音调伸缩、随机剪切、抖动等攻击的抵抗能力。     

基于内容的自适应小波域数字音频水印算法研究

以整型提升小波变换、静态图像压缩编码、人类听觉系统（HAS）为基础，提出了一种将灰度图像（即二维数字水印）嵌入到数字音频信号的新水印算法．该算法具有以下特点：（1）应用静态图像压缩编码技术，实现了以灰度图像作为水印信号的数字音频水印算法；（2）充分利用人类听觉系统（HAS），实现了二维数字水印的自适应嵌入，增强了算法的透明性和鲁棒性，（3）二维数字水印的提取不需要原始音频信号．仿真实验表明：该自适应数字音频水印算法不仅具有较好的透明性，而且对诸如叠加噪声、有损压缩、低通滤波、重新采样、重新量化等攻击均具有较好的鲁棒性．     

A robust digital audio watermarking scheme using wavelet moment invariance

It is a challenging work to design a robust audio watermarking scheme against various attacks. Wavelet moment invariances are new features combining the moment invariant features and the wavelet features, and they have some excellent characteristics, such as the ability to capture local information, robustness against common signal processing, and the linear relationship between a signal and its wavelet moments etc. Based on wavelet moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance against most attacks in this paper. Firstly, the origin digital audio is segmented and then each segment is cut into two parts. Secondly, with the spatial watermarking technique, synchronization code is embedded into the statistics average value of audio samples in the first part. And then, map 1D digital audio signal in the second part into 2D form, and calculate its wavelet moments. Finally, the watermark bit is embedded into the average value of modulus of the low-order wavelet moments. Meanwhile combining the two adjacent synchronization code searching technology, the algorithm can extract the watermark without the help from the origin digital audio signal. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signals processing such as MP3 compression, noise addition, resampling, and re-quantization etc., but also robust against the desynchronization attacks such as random cropping, amplitude variation, pitch shifting, and jittering etc.     

Audio watermarking scheme with dynamic adjustment in mute period

Watermark is some imperceptible information embedded into the work for later verification and thus it can be used to prove the originality or to protect the work from being illegally copied or modified. Kaabneh and Youssef (2001) proposed a muteness-based watermarking method for audio file. Their method can successfully embed watermarking information into audio file such that the human ears cannot distinguish the covered work from the original one. To improve the efficiency, we proposed a watermarking method for audio files in this paper. By adjusting the length of mute period dynamically, the proposed method can achieve the goal of watermark embedding with little variation of the original work. Experiment has shown that our method has the advantages of efficiency and fidelity as compared with theirs. Furthermore, it does not require the original audio file to derive the embedded watermark.     

A novel fractal image watermarking

A novel watermarking method is proposed to hide a binary watermark into image files compressed by fractal block coding. This watermarking method utilizes a special type of orthogonalization fractal coding method where the fractal affine transform is determined by the range block mean and contrast scaling. Such orthogonalization fractal decoding is a mean-invariant iteration. In contrast, the fractal parameters of classical fractal compression are very sensitive to any change of domain block pool and to common signal and geometric distortion. Hence, it is impossible to directly place a watermark in fractal parameters. The proposed watermark embedding procedure inserts a permutated pseudo-random binary sequence into the quantized range block means. The watermark is detected by computing the correlation coefficient between the original and the extracted watermark. Experimental results show that the proposed fractal watermarking scheme is robust against common signal and geometric distortion such as JPEG compression, low-pass filtering, rescaling, and clipping.     

用于MP3作品版权保护的数字水印新算法

以MP3压缩攻击特点与听觉掩蔽特性为基础，提出了一种可用于MP3音乐作品版权保护的混合域数字音频盲水印算法．首先，结合MP3压缩等攻击特点，对原始数字音频进行自适应的分段处理；再对每个音频数据段进行DWT和DCT；最后，结合听觉掩蔽特性与MP3压缩攻击特点，自适应确定量化步长，并将水印信号嵌入到音频数据段的低频分量中．仿真实验表明，所提出的算法不仅具有较好的透明性，而且对诸如重新采样、重新量化、叠加噪声、低通滤波等攻击均具有较好的鲁棒性．特别地，该算法对于最为普通的MP3压缩攻击具有极强的抵抗能力（尤其是高压缩比下）．     

一种新的基于量化的音频数字水印算法

文章提出了一种新的基于量化的音频数字水印算法,该算法首先将视觉上可辨的二值水印图像降为一维序列,再将水印序列伪随机排序,最后对数字音频信号进行分段DCT(离散余弦变换),水印信号通过量化处理过程嵌入到DCT变换后的系数中,提取水印信号无需使用原始数字音频信号。仿真实验表明水印是不可察觉的,经过mp3有损压缩、低通滤波、重采样等操作后仍具有很强的稳健性。     

A pseudo-Zernike moment based audio watermarking scheme robust against desynchronization attacks

Desynchronization attack is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust audio watermarking scheme against desynchronization attacks. Based on pseudo-Zernike moment and synchronization code, we propose a new digital audio watermarking algorithm with good auditory quality and reasonable resistance toward desynchronization attacks in this paper. Firstly, the origin digital audio is segmented and then each segment is cut into two parts. Secondly, with the spatial watermarking technique, synchronization code is embedded into the statistics average value of audio samples in the first part. And then, map 1D digital audio signal in the second part into 2D form, and calculate its pseudo-Zernike moments. Finally, the watermark bit is embedded into the average value of modulus of the low-order pseudo-Zernike moments. Meanwhile combining the two adjacent synchronization code searching technology, the algorithm can extract the watermark without the help from the origin digital audio signal. Simulation results show that the proposed watermarking scheme is not only inaudible and robust against common signals processing such as MP3 compression, noise addition, resampling, re-quantization, etc., but also robust against the desynchronization attacks such as random cropping, amplitude variation, pitch shifting, jittering, etc.     

An SVD audio watermarking approach using chaotic encrypted images

This paper presents a new approach for audio watermarking using the Singular Value Decomposition (SVD) mathematical technique. The proposed approach can be used for data hiding in the audio signals transmitted over wireless networks and for multi-level security systems as will be stated in the applications section. This approach is based on embedding a chaotic encrypted watermark in the singular values of the audio signal after transforming it into a 2-D format. The selection of the chaotic encryption algorithm for watermark encryption is attributed to its permutation nature, which resists noise, filtering, and compression attacks. After watermark embedding, the audio signal is transformed again into a 1-D format. The transformation between the 1-D and 2-D formats is performed in the well-known lexicographic ordering method used in image processing. The proposed approach can be implemented on the audio signal as a whole or on a segment-by-segment basis. The segment-by-segment implementation allows embedding the same watermark several times in the audio signal, which enhances the detectability of the watermark in the presence of severe attacks. Experimental results show that the proposed audio watermarking approach maintains the high quality of the audio signal and that the watermark extraction and decryption are possible even in the presence of attacks.     

基于Blakley方案的音频水印分存算法

提出了一种基于Blakley密钥共享方案的音频水印分存算法。算法将密钥分存的思想引入到音频水印算法中,将水印分存到音频数据的不同段中,检测时只需提取出部分水印信息就可以恢复出原始水印。算法同时采用了Bark码来解决剪切攻击带来的同步问题,并利用逼近信号统计特征和纠错码技术来提高算法的鲁棒性。实验证明,算法具有较强的抗剪切攻击能力。     

Robust multi bit and high quality audio watermarking using pseudo-random sequences

A robust multi bit and high quality audio watermarking technique in time domain is proposed in this paper. Watermarking is a technique used to label digital media by hiding copyright or other information into the underlying data. The watermark must be imperceptible and undetectable by the user and should be robust to various types of distortion. To enhance the robustness and taper-resistance of the embedded watermark, in this paper a multi bit technique is employed. Instead of embedding one bit into an audio frame, multiple bits can be embedded into each audio sub-frame. For attackers, since they do not know the parameters, this significantly reduces the possibility of unauthorized bit detection and removal of watermark. In real-time watermarking applications, robustness is not the only factor that plays an important role. The other factor that plays a very an important role is computational complexity. In general, audio file is transmitted in compressed form. Real-time watermark embedding must take into account this compressed form, because first decompressing the data, adding a watermark and then recompressing the data is computationally too demanding. In this paper, we propose robust and low complexity audio watermarking algorithm. To evaluate the performance of the proposed audio watermarking algorithm, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) were conducted. Compared to traditional one bit embedding algorithm, the proposed algorithm gives highly recovery rate after attack by commonly used audio data manipulations, such as low pass filtering, requantization, resampling, and MP3 compression.     

基于小波域的均值量化数字音频水印算法

提出了一种均值量化的小波域数字音频水印算法。均值量化可以减少攻击对水印的影响,算法选择合适的小波基对音频信号进行小波分解,对其中的中、低频系数进行均值量化,嵌入水印,水印提取过程不需要原始音频信号。实验结果表明,与一般水印量化算法相比,该算法对MP3、重量化、重采样、低通滤波和噪声干扰等信息处理型攻击具有更好的鲁棒性。     

基于重心的抗同步攻击的音频水印算法

抗同步攻击是音频水印领域公开的难题. 相对重心是音频的一个稳定的全局特征量, 对 TSM (Time scale modification)等同步攻击不敏感. 本文提出一种基于相对重心的抗同步攻击的音频水印算法,提出的算法通过量化音频的相对重心生成水印, 生成的水印由混沌序列加密后以量化的方法嵌入载体音频三级小波近似分量均值中. 为了降低同步攻击后同步位置的连续偏移, 水印嵌入提取过程采用了均匀分帧的方法. 实验结果表明提出的算法能抵抗常规信号处理操作, 同时 能抵抗20%的TSM操作(包含音调不变TSM和重采样操作)和 1/10的抖动操作, 有很好的鲁棒性.     

基于陷阱策略的音频数字水印新方法

数字水印已经成为实现多媒体版权保护的一项重要技术.提出在嵌入鲁棒性水印的同时考虑攻击的行为特征,辅以陷阱策略抵制各种攻击.水印以量化音频DCT系数的方式嵌入,在提取时针对攻击的行为特征以不同方式提取水印.算法嵌入的水印为一幅二值图像,能抵制随机裁剪、AD及DA转换、低通滤波等去同步型攻击,提取的水印可以直接分辨.与cocktail水印方法相比,所提方法的鲁棒性高,提取水印时不需要原始音频.实验结果说明我们的音频水印方法十分有效.