音频数字水印与隐写分析算法研究
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摘要
随着互联网应用的普及,越来越多的数字化多媒体内容信息纷纷以各种形式在网络上快速的交流和传播。如何对数字化多媒体内容进行有效的管理和保护,成为信息安全领域的研究热点。多媒体数字内容在网络上的传递、发布和扩散带来了一系列问题和应用需求,从总体上来说可以分为两大部分：多媒体数字内容的版权保护问题和伪装式保密通信。
对于上述问题和需求,人们最初的想法是求助于传统的密码学,但是传统的加密手段无法解决上述问题。为此,人们开始寻找新的解决办法来作为对传统密码系统的补充。信息隐藏可以在载体中嵌入难以被感知的秘密信息以保护数字内容的版权或用于保密通信,可以很好的解决上述问题。数字水印和隐写术是信息隐藏的两个重要研究分支,用于信息隐藏的载体可以是图像、视频、音频、文本和网络协议等。
音频数字水印是在音频中嵌入与音频载体有关的信息来保护数字音频,音频隐写术主要是把需要传递的秘密信息隐藏在看似正常的音频载体中,以隐藏秘密信息的存在性,用于保密通信。音频数字水印和隐写术的研究课题可分为正向研究和逆向研究。基于音频的隐写术和数字水印的研究是正向研究,音频数字水印主要是研究在音频中嵌入和提取水印的各种算法。基于音频的水印攻击和隐写分析是逆向研究,音频水印攻击的目标是妨碍水印信息顺利提取。音频隐写术主要是研究如何在音频载体中隐藏秘密信息用于保密通信。隐写分析的目标是判断和检测听觉上正常的音频载体中是否隐藏秘密信息。
本文的研究工作主要集中在音频的数字水印和隐写分析领域,提出两种变换域音频水印算法和两种专用的音频隐写分析算法。本文工作主要包括以下四个方面。
1.提出一种结合离散小波变换、离散余弦变换和奇异值分解的音频盲水印算法。算法首先将音频分段,每段音频进行一维小波变换,取出近似分量。将近似分量进行离散余弦变换,将变化后前四分之一的系数取出转成二维矩阵A,对A进行奇异值分解,利用奇异值分解后S矩阵的S(1,1)和S(2,2)的比值关系在S(1,1)中嵌入水印信息。奇异值分解后S矩阵的调整不会对矩阵A产生较大影响,因此该算法具有较好的透明性。该算法将水印信息嵌入在离散小波变换后的近似分量,算法具有较好的鲁棒性。同时S矩阵具有较强的稳定性,矩阵A的变化也不会对S矩阵的值产生较大影响,因此该算法能抵抗各种常规音频信号处理攻击。实验表明该算法具有较好的透明性,同时对MP3压缩、重采样、重量化、加噪、低通滤波和裁剪替换等常规音频信号处理攻击具有较强的鲁棒性。
2.提出一种用于音频内容完整性保护的离散小波变换域半脆弱音频水印算法。该算法对原始音频进行一维小波变换后取出近似分量,计算所有近似分量的平均值作为量化步长,然后将音频近似分量分段,将每段近似分量的平均值进行量化处理后嵌入置乱后的二值图像水印信息。该算法具有很好的透明性,实验表明该算法能容忍如加噪、MP3压缩、重采样和低通滤波等常规音频信号处理。作为音频内容完整性保护的半脆弱音频水印算法,该算法能检测出静音替换、使用原始音频代替含水印音频、甚至是两种替换组合的恶意篡改,而且还能准确定位篡改位置,实验表明该算法恶意篡改定位误判率低于8%。
3.提出一种离散余弦变换音频隐写的专用隐写分析算法。通过对隐写算法分析得出隐写算法改变了分段信号的均值,利用音频均值为正、负的分段数目差值比例来判断音频是否为隐写音频。检测的方法是对所有待检测音频进行二次隐写,自然音频二次隐写前后的均值为正、负的分段数目差值比例的值明显高于隐写音频,通过差值比例和阈值比较判断待检测音频是否为隐写音频。实验结果表明该算法的准确率为80.6%。
4.提出一种基于回声隐藏的专用隐写分析算法。该算法基于回声隐藏改变自然语言倒谱分布这一特点,通过构造倒谱和差分方差VDSC (Variants of Difference of Sum of Cepstrum)来反映隐写对自然音频的影响,并据此来判断该音频文件是否为隐写音频。分析过程在不同的偏移条件下计算待检测音频的VDSC值,如果VDSC的值没有显著变化,且在相对判决域以下,则该待检测音频为自然音频。如果计算出来的VDSC值有显著变化,且在相对判决域以上,则该待检测音频为隐写音频。实验结果表明该算法准确率为88.2%。
With the popularity of Internet applications, the transmission opportunities of multimedia data become increasing. How to manage and protect these multimedia data has attracted more attentions in the field of information security. Lots of problems and application requirements raise when the digital content distributes on networks, which generally can be divided into two parts:the copyright protection and camouflage confidential communication.
Initially, the researchers want to use traditional cryptography to solve the security problems of multimedia content. But the traditional encryption methods can not meet its requirements. So the researchers begin to look for new solutions as a complement for the traditional cryptography. Information hiding is a new solution for the security of digital media content, which embeds secret information into digital carrier imperceptibility. Digital watermarking and steganography are two important branches of inforamtaion hiding. The carrier can be digital graph, audio, video, text and network protocol.
Audio digital watermarking embeds the secret message which related with the audio into the audio to protect the audio file. Steganography embeds the secret message to hide the existence of the hidden message for confidential communication. According to the research achievements at present, audio information hiding can be roughly divided into four aspects: digital watermarking, watermarking attack, steganography and steganalysis. Audio watermarking algorithm focuses on kinds of audio watermark embedding and extracting watermarking algorithms. Audio watermarking attack mainly research on various attack methods to audio watermarking, which target is that obstacle the watermark information extracted smoothly. Audio steganographic methods mainly research on various algorithms used to hide the secret information in audio carrier used for confidential communication. Steganalysis is the opposite aspect of Steganography, which mainly studies various technical analysis algorithms. The algorithms are used to judge the audio is the stego audio or not.
This dissertation focuses on audio digital watermarking and steganalysis, and proposes two novel audio watermarking algorithms and two novel specific audio steganalysis algorithms. The main content of this dissertation is summarized as follows:
1. A novel DWT-DCT-SVD based audio blind watermarking algorithm is proposed. In this algorithm, the audio is split into non-overlapping frames, and each frame is decomposed on one-dimensional discrete wavelet transform (DWT), then the approximate sub-band coefficients are decomposed on discrete cosine transform (DCT) and partitioned into2-D matrix A for the first quarter of the DCT coefficients, then A decomposed on singular value decomposition (SVD) and get a diagonal matrix S. the watermarking information is embedded into S(1,1) according the ratio of S(1,1) and S(2,2). The change of S-matrix does not affect the value of matrix A, the algorithm has good transparency. The algorithm has better robustness because the watermark information is embedded in the approximate sub-band coefficients. S-matrix has a strong stability, and the change of matrix A does not greatly affect the value of S-matrix, so the algorithm can resist all kinds of common audio signal processing attacks. The experiments show that the algorithm has strong robustness against the common audio signal processing such as additive white Gaussian noise, MP3compression, resampling, low-pass filtering, requantization, cropping and denoising.
2. A new DWT-based semi-fragile audio watermarking algorithm used for content authentication is proposed. In this algorithm, the original audio is decomposed on three layers DWT transform to get DWT approximation coefficients. Then the values of all approximate coefficients are computed and as the quantization step. Then the approximate coefficients are split into non-overlapping blocks, and the mean value of each approximate component block is quantized and embedded watermark information. The transparency of this algorithm is excellent and can tolerate MP3compression, Re-sampling, low-pass filter and other conventional signal processing. As a content authentication algorithm, this algorithm can accurately detect the replacing positions from mute replaced, or using natural audio instead of the Stego audio, or even two methods with combination. The accuracy of this algorithm is6%
3. A novel specific steganalysic algorithm based on DCT is proposed. The analysis of the Steganography changed the statistical characteristics of DCT coefficient symbols. Based on this, a new difference ratio steganalysis algorithm is proposed. The detection method is to make all test carriers have second Steganography. Since the DR value proportion of the natural audio is significantly higher than that of Stego audio before and after the second Steganography, then the threshold testing could judge whether the carrier is the Stego audio. The experiment results show that the accuracy of this algorithm is80.6%.
4. A novel special steganalysis algorithm based on echo hiding is proposed. Based on the specialty that echo hiding alter nature language epstrum distribution, this algorithm constructs cepstrum and difference variance of VDSC (Variants of Sum of Cepstrum) to reflect the influence of steganalysis algorithm to natural audio, which can be used to judge whether the test audio is stego audio. Analyzing process uses different migration conditions to calculate VDSC value of the testing carrier. If there is no significant change of the VDSC values and it is below the value of relative judgment domain, the test audio is the original audio. If there is significant change of the VDSC values and it is above the value of relative judgment domain, then the test audio is the stego audio. The experiment shows that the accuracy of this algorithm is88.2%.
对于上述问题和需求,人们最初的想法是求助于传统的密码学,但是传统的加密手段无法解决上述问题。为此,人们开始寻找新的解决办法来作为对传统密码系统的补充。信息隐藏可以在载体中嵌入难以被感知的秘密信息以保护数字内容的版权或用于保密通信,可以很好的解决上述问题。数字水印和隐写术是信息隐藏的两个重要研究分支,用于信息隐藏的载体可以是图像、视频、音频、文本和网络协议等。
音频数字水印是在音频中嵌入与音频载体有关的信息来保护数字音频,音频隐写术主要是把需要传递的秘密信息隐藏在看似正常的音频载体中,以隐藏秘密信息的存在性,用于保密通信。音频数字水印和隐写术的研究课题可分为正向研究和逆向研究。基于音频的隐写术和数字水印的研究是正向研究,音频数字水印主要是研究在音频中嵌入和提取水印的各种算法。基于音频的水印攻击和隐写分析是逆向研究,音频水印攻击的目标是妨碍水印信息顺利提取。音频隐写术主要是研究如何在音频载体中隐藏秘密信息用于保密通信。隐写分析的目标是判断和检测听觉上正常的音频载体中是否隐藏秘密信息。
本文的研究工作主要集中在音频的数字水印和隐写分析领域,提出两种变换域音频水印算法和两种专用的音频隐写分析算法。本文工作主要包括以下四个方面。
1.提出一种结合离散小波变换、离散余弦变换和奇异值分解的音频盲水印算法。算法首先将音频分段,每段音频进行一维小波变换,取出近似分量。将近似分量进行离散余弦变换,将变化后前四分之一的系数取出转成二维矩阵A,对A进行奇异值分解,利用奇异值分解后S矩阵的S(1,1)和S(2,2)的比值关系在S(1,1)中嵌入水印信息。奇异值分解后S矩阵的调整不会对矩阵A产生较大影响,因此该算法具有较好的透明性。该算法将水印信息嵌入在离散小波变换后的近似分量,算法具有较好的鲁棒性。同时S矩阵具有较强的稳定性,矩阵A的变化也不会对S矩阵的值产生较大影响,因此该算法能抵抗各种常规音频信号处理攻击。实验表明该算法具有较好的透明性,同时对MP3压缩、重采样、重量化、加噪、低通滤波和裁剪替换等常规音频信号处理攻击具有较强的鲁棒性。
2.提出一种用于音频内容完整性保护的离散小波变换域半脆弱音频水印算法。该算法对原始音频进行一维小波变换后取出近似分量,计算所有近似分量的平均值作为量化步长,然后将音频近似分量分段,将每段近似分量的平均值进行量化处理后嵌入置乱后的二值图像水印信息。该算法具有很好的透明性,实验表明该算法能容忍如加噪、MP3压缩、重采样和低通滤波等常规音频信号处理。作为音频内容完整性保护的半脆弱音频水印算法,该算法能检测出静音替换、使用原始音频代替含水印音频、甚至是两种替换组合的恶意篡改,而且还能准确定位篡改位置,实验表明该算法恶意篡改定位误判率低于8%。
3.提出一种离散余弦变换音频隐写的专用隐写分析算法。通过对隐写算法分析得出隐写算法改变了分段信号的均值,利用音频均值为正、负的分段数目差值比例来判断音频是否为隐写音频。检测的方法是对所有待检测音频进行二次隐写,自然音频二次隐写前后的均值为正、负的分段数目差值比例的值明显高于隐写音频,通过差值比例和阈值比较判断待检测音频是否为隐写音频。实验结果表明该算法的准确率为80.6%。
4.提出一种基于回声隐藏的专用隐写分析算法。该算法基于回声隐藏改变自然语言倒谱分布这一特点,通过构造倒谱和差分方差VDSC (Variants of Difference of Sum of Cepstrum)来反映隐写对自然音频的影响,并据此来判断该音频文件是否为隐写音频。分析过程在不同的偏移条件下计算待检测音频的VDSC值,如果VDSC的值没有显著变化,且在相对判决域以下,则该待检测音频为自然音频。如果计算出来的VDSC值有显著变化,且在相对判决域以上,则该待检测音频为隐写音频。实验结果表明该算法准确率为88.2%。
With the popularity of Internet applications, the transmission opportunities of multimedia data become increasing. How to manage and protect these multimedia data has attracted more attentions in the field of information security. Lots of problems and application requirements raise when the digital content distributes on networks, which generally can be divided into two parts:the copyright protection and camouflage confidential communication.
Initially, the researchers want to use traditional cryptography to solve the security problems of multimedia content. But the traditional encryption methods can not meet its requirements. So the researchers begin to look for new solutions as a complement for the traditional cryptography. Information hiding is a new solution for the security of digital media content, which embeds secret information into digital carrier imperceptibility. Digital watermarking and steganography are two important branches of inforamtaion hiding. The carrier can be digital graph, audio, video, text and network protocol.
Audio digital watermarking embeds the secret message which related with the audio into the audio to protect the audio file. Steganography embeds the secret message to hide the existence of the hidden message for confidential communication. According to the research achievements at present, audio information hiding can be roughly divided into four aspects: digital watermarking, watermarking attack, steganography and steganalysis. Audio watermarking algorithm focuses on kinds of audio watermark embedding and extracting watermarking algorithms. Audio watermarking attack mainly research on various attack methods to audio watermarking, which target is that obstacle the watermark information extracted smoothly. Audio steganographic methods mainly research on various algorithms used to hide the secret information in audio carrier used for confidential communication. Steganalysis is the opposite aspect of Steganography, which mainly studies various technical analysis algorithms. The algorithms are used to judge the audio is the stego audio or not.
This dissertation focuses on audio digital watermarking and steganalysis, and proposes two novel audio watermarking algorithms and two novel specific audio steganalysis algorithms. The main content of this dissertation is summarized as follows:
1. A novel DWT-DCT-SVD based audio blind watermarking algorithm is proposed. In this algorithm, the audio is split into non-overlapping frames, and each frame is decomposed on one-dimensional discrete wavelet transform (DWT), then the approximate sub-band coefficients are decomposed on discrete cosine transform (DCT) and partitioned into2-D matrix A for the first quarter of the DCT coefficients, then A decomposed on singular value decomposition (SVD) and get a diagonal matrix S. the watermarking information is embedded into S(1,1) according the ratio of S(1,1) and S(2,2). The change of S-matrix does not affect the value of matrix A, the algorithm has good transparency. The algorithm has better robustness because the watermark information is embedded in the approximate sub-band coefficients. S-matrix has a strong stability, and the change of matrix A does not greatly affect the value of S-matrix, so the algorithm can resist all kinds of common audio signal processing attacks. The experiments show that the algorithm has strong robustness against the common audio signal processing such as additive white Gaussian noise, MP3compression, resampling, low-pass filtering, requantization, cropping and denoising.
2. A new DWT-based semi-fragile audio watermarking algorithm used for content authentication is proposed. In this algorithm, the original audio is decomposed on three layers DWT transform to get DWT approximation coefficients. Then the values of all approximate coefficients are computed and as the quantization step. Then the approximate coefficients are split into non-overlapping blocks, and the mean value of each approximate component block is quantized and embedded watermark information. The transparency of this algorithm is excellent and can tolerate MP3compression, Re-sampling, low-pass filter and other conventional signal processing. As a content authentication algorithm, this algorithm can accurately detect the replacing positions from mute replaced, or using natural audio instead of the Stego audio, or even two methods with combination. The accuracy of this algorithm is6%
3. A novel specific steganalysic algorithm based on DCT is proposed. The analysis of the Steganography changed the statistical characteristics of DCT coefficient symbols. Based on this, a new difference ratio steganalysis algorithm is proposed. The detection method is to make all test carriers have second Steganography. Since the DR value proportion of the natural audio is significantly higher than that of Stego audio before and after the second Steganography, then the threshold testing could judge whether the carrier is the Stego audio. The experiment results show that the accuracy of this algorithm is80.6%.
4. A novel special steganalysis algorithm based on echo hiding is proposed. Based on the specialty that echo hiding alter nature language epstrum distribution, this algorithm constructs cepstrum and difference variance of VDSC (Variants of Sum of Cepstrum) to reflect the influence of steganalysis algorithm to natural audio, which can be used to judge whether the test audio is stego audio. Analyzing process uses different migration conditions to calculate VDSC value of the testing carrier. If there is no significant change of the VDSC values and it is below the value of relative judgment domain, the test audio is the original audio. If there is significant change of the VDSC values and it is above the value of relative judgment domain, then the test audio is the stego audio. The experiment shows that the accuracy of this algorithm is88.2%.
引文
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