An efficient singular value decomposition algorithm for digital audio watermarking

The singular value decomposition (SVD) mathematical technique is utilized, in this paper, for audio watermarking in time and transform domains. Firstly, the audio signal in time or an appropriate transform domain is transformed to a 2-D format. The SVD algorithm is applied on this 2-D matrix, and an image watermark is added to the matrix of singular values (SVs) with a small weight, to guarantee the possible extraction of the watermark without introducing harmful distortions to the audio signal. The transformation of the audio signal between the 1-D and 2-D formats is performed in the well-known lexicographic ordering method used in image processing. A comparison study is presented in the paper between the time and transform domains as possible hosting media for watermark embedding. Experimental results are in favor of watermark embedding in the time domain if the distortion level in the audio signal is to be kept as low as possible with a high detection probability. The proposed algorithm is utilized also for embedding chaotic encrypted watermarks to increase the level of security. Experimental results show that watermarks embedded with the proposed algorithm can survive several attacks. A segment-by-segment implementation of the proposed SVD audio watermarking algorithm is also presented to enhance the detectability of the watermark in the presence of severe attacks.     

Efficient SVD speech watermarking with encrypted images

This paper presents a new approach for speech signal watermarking using encrypted watermarks. The objective of this approach is to increase the degree of security of speech watermarking. In the proposed framework, watermark embedding is implemented with singular value decomposition due to its robustness to attacks. Moreover, two encryption schemes are tested for watermark image encryption; chaotic encryption due to its permutation nature and data encryption standard (DES) due to its diffusion nature. Overall and block-by-block watermarking scenarios are tested and compared for speech signal watermarking. Different modes of operation of the DES are investigated for watermark image encryption. These modes are the electronic code book, cipher block chaining, cipher feedback, and output feedback (OFB) modes. Simulation results reveal that the DES with OFB mode and the chaotic Baker map encryption make the system less sensitive to attacks with good quality of extracted watermarks.     

基于混沌序列的多重数字图像水印算法

采用一维混沌映射，根据不同的混沌初始条件生成多个互不相关的混沌实值序列，进而得到性能良好的多重数字图像水印信号，有效地解决了多重数字图像水印信号的构造问题．同时采用二维混沌映射将各水印信号置乱，随机均匀地叠加在图像小波变换的中低频系数上，各水印信号的嵌入和提取可以互不干扰，解决了多重数字图像水印的嵌入问题．实验结果表明，该算法对各种常见的攻击均具备了一定的抵抗能力，可有效地解决数字图像产品的多著作权问题．     

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.     

一种抗剪切的DWT域多重音频数字水印算法

提出了一种能够抵抗剪切攻击的鲁棒性DWT域多重音频数字水印算法。该算法结合音频分帧技术及小波变换理论,将置乱、降维处理后的不同彩色数字图像信息嵌入到宿主音频信号的低频小波系数中,实现了多重彩色图像水印在宿主音频中的嵌入与提取。实验结果表明,该算法不仅能够较好地抵抗常规攻击,对剪切攻击也具有较强的鲁棒性,即使是在受到强剪切攻击后仍然能够提取出较清晰的(多重)水印信号。     

一种基于改进的分段DCT域多格式音频水印算法

针对因为格式种类庞大而导致音频文件数字水印的嵌入较复杂且繁琐的问题, 采取了利用FFMPEG将音频文件转换成一种统一格式而进行数字水印嵌入的方法, 其效率和效果有较大提高。对于水印算法提出了一种改进的分段DCT算法, 将二维的水印图像转换成一维数字序列并进行置乱加密和极化操作, 然后对数字音频信号作分段DCT变换, 根据每段的能量不同采取不同等级的嵌入强度, 其中选取四个不同等次的系数进行反复嵌入。实验仿真表明, 在经过格式转换后的音频文件与原始文件之间没有出现失真, 该算法在经过加入高斯白噪声、低通滤波、有损压缩等操作后仍具有很强的稳健性。     

基于ANFIS的倒谱域盲检测混沌音频水印算法

倒谱分析广泛运用于音频信号处理的很多方面,但目前研究倒谱域音频水印算法的文献很少,而且现有的水印算法大多没有实现盲检测,不利于实际运用。该文提出了一种具有较高鲁棒性的混沌音频水印算法,并通过自适应神经网络模糊推理系统(AdaptiveNeuro-FuzzyInferenceSystem,ANFIS)实现了盲检测。实验证明,该算法的水印嵌入易实现,水印检测准确性高,时间代价小,具有较强的抗攻击性和较好的不可感知性,很有实用价值。     

Efficient audio integrity verification algorithm using discrete cosine transform

Audio recordings have been used as evidence for long times. Multimedia processing advancement makes it difficult to be completely sure about what is heard is the truth. This paper presents a promising approach for integrity verification of recorded audio signals using discrete cosine transform. This approach is based on self embedding concept which embeds block-based marks extracted from the same audio signal after being transformed into 2-D format into other blocks according to a specific algorithm. After the self-embedding process, the data is converted back into 1-D style which represents a marked audio signal. The 1-D audio signal is converted into a 2-D format and then converted back into a 1-D format using the popular lexicographic ordering scheme utilized in image processing. Reverse processes are executed to extract the verification marks from the audio signal throughout the integrity verification process. Based on the extracted audio signal properties, the integrity of the marked audio signal is evaluated. Different audio processing tasks and attacks are implemented to examine the suitability of the proposed algorithm for verifying the integrity of high-confidentiality recorded audio data. The results show that the efficient ability of the proposed approach to verify integrity and detect attacks.     

An optimized high payload audio watermarking algorithm based on LU-factorization

In the field of audio watermarking, reliably embedding the large number of watermarking bits per second in an audio signal without affecting the audible quality of the host audio with good robustness against signal processing attacks is still one of the most challenging issues. In this paper, a high payload, perceptually transparent and robust audio watermarking solution for such a problem by optimizing the existing problem using genetic algorithm is presented. The genetic algorithm in this paper is used to find the optimal number of audio samples required for hiding each watermarking bit. The embedding is done using the imperceptible properties of LU (lower upper) factorization in wavelet domain. This paper addresses the robustness within perceptual constraints at high payload rate in both mathematical analysis and experimental testing by representing behavior of various attacks using attack characterization. Experimental results show that the proposed audio watermarking algorithm can achieve 1280 bps capacity at an average Signal-to-noise ratio (SNR) of 31.02 dB with good robustness to various signal processing attacks such as noise addition, filtering, and compression. In addition, the proposed watermarking algorithm is blind as it does not require the original signal or watermark during extraction. The comparison of the proposed algorithm with the existing techniques also shows that the proposed algorithm is able to achieve high payload with good robustness under perceptual constraints.     

A learning-based audio watermarking scheme using kernel Fisher discriminant analysis

A novel learning-based audio watermarking scheme using kernel Fisher discriminant analysis (KFDA) is proposed in this paper. Two techniques, down-sampling technique and energy relationship modulation technique, are developed in order to guarantee good fidelity of the watermarked audio signal. At the same time, local energy relationship between audio sub-frames is hid in the watermarked audio signal with watermark embedding. Moreover, a learning-based watermark detector using the KFDA is exploited and it extracts the watermark by learning the local energy relationship hid in the watermarked audio signal. Due to powerful non-linear learning ability and good generalization ability of the KFDA, the learning-based watermark detector can exhibit high robustness against common audio signal processing or attacks compared with other audio watermarking methods. In addition, it also has simple implementation and lower computation complexity.     

Audio watermarking scheme based on embedding strategy in low frequency components with a binary image

With the recent development of information technology and computer network, digital format of data has become more and more popular. However, a major problem faced by digital data providers and owners is protecting data from unauthorized copying and distribution. As a solution to the problem, digital watermark technology is now attracting attention as new method of protection against said unauthorized copying and distribution. The aim of the digital audio watermarking is to take prespecified data that carries certain information and hide it within the audio stream such that it is not audible to the human ear (i.e., transparent) but at the same time renders the file more resistant to removal (i.e., robust). In this paper, we propose a new method for embedding digital watermarks into audio signals in low frequency components, which method mitigates these and other related shortcomings. The proposed method uses the wavelet transform constructed by lifting-based wavelet transform (LBWT) in order to provide a fast implementation between watermark embedding and extraction parts. In the first stage of the proposed method, the original audio host signal is converted to a wavelet domain using LBWT. The signal is thus decomposed into low and high frequency components. Approximation coefficients correspond to low frequency components of the signal. Next, the watermark generated by pseudorandom numbers is embedded into wavelet approximation coefficients of the segmented host audio signal depending on the binary value of the binary image. The reason for embedding the watermark in the low frequency components is that these components' energy is greater than that of high frequency components in such a way that the watermark is inaudible; therefore, it should not alter the audible content and should not be easy to remove. The proposed method uses a binary image to decide whether or not the watermark generated by pseudorandom numbers is embedded in the audio host signal. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including bit error rate (BER) and signal-to-noise ratio (SNR) are conducted. The tests' results show that the proposed method yields a high recovery rate after attacks by commonly used audio data manipulations such as low-pass filtering, requantization, resampling and MP3 compression.     

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。     

基于纠错编码的自适应图像水印算法

采用三维Lorenz映射对水印加密以提高安全性,并通过纠正水印误码来降低检测误码率,提高水印的稳健性.充分考虑了纠错编码中引入的信息冗余将导致水印嵌入强度的降低等问题,采用基于蚁群算法的图像内容边缘检测方法,使水印的分布集中在图像显著的边缘特征中,嵌入强度随着图像特征的变化而自适应地变化.在水印的检测中,利用Kalman滤波法对水印信息进行预测和估计,在没有原始图像数据的情况下,能够恢复嵌入的信息.实验结果表明,该方案具有较好的抗JPEG压缩、高斯噪声和剪切的鲁棒性.     

一种基于非均匀离散傅立叶变换的鲁棒音频水印算法

基于离散傅立叶变换（DFT）的音频水印算法对常规信号处理操作具有较高的鲁棒性，然而，在DFT域的固定频率点嵌入水印信息易受频域攻击，导致此类水印算法存在安全隐患．为进一步说明这种安全隐患，本文描述了一种新颖的频域攻击方法，仿真结果表明采用该方法可以在不影响含水印音频信号听觉感知质量的条件下有效去除水印信息．针对上述问题，本文提出了一种基于非均匀离散傅立叶变换（NDFT）的鲁棒音频水印算法．该算法基于NDFT可以任意选择频率点的特性，利用混沌映射随机选取NDFT域的水印嵌入频率点，以实现水印嵌入位置的随机性．此外，引入另一个混沌映射置乱加密待嵌入的水印信息以提高算法抵抗拷贝攻击的能力．理论分析和实验结果表明该算法不仅具有抗常规信号处理操作高的鲁棒性，而且能够抵抗频域的恶意攻击，大的密钥空间保证了系统高安全性．     

一种易损性音频数字水印技术

利用变换域嵌入水印是音频水印的主流技术,一般的嵌入方法是通过调整所选变换系数实现。谱弯折方法实现整段频谱的非线性位移,可将水印嵌入整个频谱。该文在Choi犤1犦的谱弯折音频数字水印算法基础上,研究了算法的鲁棒性,通过大量实验验证,认为谱弯折算法对信号处理类攻击相当脆弱,不具备鲁棒性,是一种易损性音频水印。     

一种基于混沌加密的DWT数字音频水印算法

提出一种基于混沌加密的DWT数字音频水印算法。算法从水印的安全性出发,水印信息加密过程引入混沌理论,第一次加密过程利用二维映射对水印信息进行置乱加密,再利用高维混沌系统对得到的第一次加密后的水印进行二次加密。为了提高算法鲁棒性,采用同时嵌入多个同一水印信息的方式,通过少数服从多数的原则来确定提取出的水印信息,进而增强水印信息的纠错能力,提高水印的鲁棒性。仿真实验结果及数据分析表明该算法具有较好的鲁棒性及安全性。     

Decode-Time Forensic Watermarking of AAC Bitstreams

In digital rights-management systems, forensic watermarking complements encryption and deters the capture and unauthorized redistribution of the rendered content. In this paper, we propose a novel watermarking method which is integrated into the advanced audio coding (AAC) standard's decoding process. For predefined frequency bands, the method intercepts and modifies the scale factors, which are utilized for dequantization of spectral coefficients. It thereby modulates the short-time envelope of the bandlimited audio and embeds a watermark which is robust to various attacks, such as capture with a microphone and recompression at lower bit rates. Inclusion of watermark embedding in the AAC decoder has practically no effect on the decoding complexity. As a result, the proposed method can be integrated even into resource-constrained devices, such as portable players without any additional hardware.     

基于混沌加密和误差扩散控制的AVS压缩域视频水印*

针对压缩域视频水印安全性与误差积累问题,提出一种基于AVS压缩域的水印新算法。针对误差积累问题,提出两种控制方法,最大限度地降低了误差积累。此外,对嵌入前的水印进行了混沌处理,提高了水印的安全性。仿真实验结果表明,误差积累得到很好的控制,满足盲检性和不可见性。     

基于心理声学模型的盲音频数字水印改进型算法

以往基于离散小波变换的音频数字水印算法鲁棒性不强,无法对数字音频信号的版权进行真正地保护,因此改进了算法,利用心理声学模型,控制水印信号的嵌入,通过计算音频信号的掩蔽阀值,在保证水印嵌入不可察觉的前提下,增大水印的嵌入强度。仿真实验证明,该算法具有较强的鲁棒性和不可感知性,能有效抵御各种常见攻击,并且能实现盲检测。     

基于对象传播神经网络的抗TSM攻击音频水印算法*

提出了一种基于对象传播神经网络的抗TSM攻击音频水印算法。利用CPN自学习和自适应的特征,通过自适应改变段长的分段算法,选用具有较强稳定性的小波低频系数方差作为输入向量训练CPN,建立音频特征与水印信号的对应关系,以达到嵌入水印的目的。实验结果表明,该算法对常规音频信号处理和TSM等同步攻击具有很强的鲁棒性。