基于小波变换的音频隐写算法研究
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摘要
随着网络音频文件的广泛传播,以及信息安全领域面临的严峻形势,音频隐写技术已经受到越来越多的关注。本文在分析总结音频隐写技术当前的研究现状与存在的问题后,主要围绕在保证不可感知性和鲁棒性的前提下,提高隐秘信息嵌入容量问题展开研究,在小波域设计了两种不同的音频隐写算法。
首先,针对传统直接相加、量化编码,以及修改能量比等嵌入方法存在的嵌入量难以提升的问题,引入矩阵编码的嵌入方法。该方法的特点是能够大幅提高嵌入效率,从而达到提高嵌入量的目的。并且矩阵编码有助于减小对原始音频的修改比例,进而减小嵌入数据对原始音频载体不可感知性的影响。为了改善传统一代小波运算量大,执行速度慢的问题,算法选择提升小波变换系数来嵌入数据。考虑到要保证保密语音的绝对隐蔽,算法利用MPEG I心理声学模型1来计算掩蔽阈值,由掩蔽阈值来控制嵌入帧。
其次,针对以往嵌入方法对小波系数浮点数直接处理存在的难以精确控制的问题,引入PCM量化编码将小波系数分段均值量化为二进制序列。该方法可极大减小量化误差,比传统普通单值量化法具有更强的鲁棒性。算法仍然利用矩阵编码的嵌入方法,是对每一个小波分段均值而言,根据应用需求设定分段大小,则可实现嵌入容量的提高。为了降低运算量,算法利用复杂度较低的音频信号时频分析,通过寻找浊音帧来选择嵌入帧,不可感知性亦能得到保证。
通过实验分析,本文提出的两种小波域音频隐写算法较同类算法具有较高的嵌入容量,并保证了良好的鲁棒性和不可感知性。
With widely disseminating of network audio document and the serious situation in the information security field, the audio steganography have been under more and more attention. This paper analyzes and summarized the current research status and existing problems of the audio steganography, then the major focus is around ensuring imperceptibility and robustness to enhance the capacity of hidden information embedded, and designs two kind of audio steganography algorithm in wavelet domain.
Firstly, according to the problem that some embeding methods such as plusing directly, quantization coding, modifing the energy ratio and so on are difficult to enhancing the embeding capacity, so the matrix coding is introducted. This method's characteristic is capable of greatly improving the embeding efficiency, so as to achieve the purpose of raising the embeding capacity. And the matrix coding help to reduce the proportion of the original audio changes, thereby reducing the effects of the original audio carrier'imperceptibility when embeded datas. In order to improve the problems as large calculation amount and slow execution speed of the traditional generation wavelet, the algorithm chooses the lifting wavelet transform coefficients to embed datas. Considering ensuring absolute concealment of the secret speech, the algorithm uses MPEG I Audio Psychoacoustic model 1 to compute masking threshold, and controls the embedded frames by masking threshold.
Secondly, according to the previous embeding methods's problem of the difficult controling to the wavelet coefficient's floating point numbers caused by processing directly, the PCM quantization coding is introducted to quantify the every segment's mean value of wavelet coefficient to a binary sequence. This method can greatly reduce the quantization error, and have stronger robustness than traditional ordinary single-valued quantization. The algorithm still uses the matrix coding embeding method, but it's for every segment's mean value of wavelet coefficient. Section size set according to application needs, you can achieve the embedding capacity to improve. In order to induce the calculation amount, the algorithm uses the less complex time-frequency analysis of audio signals to select the embedded frame by looking for voiced frame, imperceptibility can also be guaranteed.
Through the experimental analysis, the two kinds of wavelet domain audio steganography algorithm presented in this paper have higher embeding capacity than the same kind of algorithms, and guarantee a good robustness and imperceptibility.
首先,针对传统直接相加、量化编码,以及修改能量比等嵌入方法存在的嵌入量难以提升的问题,引入矩阵编码的嵌入方法。该方法的特点是能够大幅提高嵌入效率,从而达到提高嵌入量的目的。并且矩阵编码有助于减小对原始音频的修改比例,进而减小嵌入数据对原始音频载体不可感知性的影响。为了改善传统一代小波运算量大,执行速度慢的问题,算法选择提升小波变换系数来嵌入数据。考虑到要保证保密语音的绝对隐蔽,算法利用MPEG I心理声学模型1来计算掩蔽阈值,由掩蔽阈值来控制嵌入帧。
其次,针对以往嵌入方法对小波系数浮点数直接处理存在的难以精确控制的问题,引入PCM量化编码将小波系数分段均值量化为二进制序列。该方法可极大减小量化误差,比传统普通单值量化法具有更强的鲁棒性。算法仍然利用矩阵编码的嵌入方法,是对每一个小波分段均值而言,根据应用需求设定分段大小,则可实现嵌入容量的提高。为了降低运算量,算法利用复杂度较低的音频信号时频分析,通过寻找浊音帧来选择嵌入帧,不可感知性亦能得到保证。
通过实验分析,本文提出的两种小波域音频隐写算法较同类算法具有较高的嵌入容量,并保证了良好的鲁棒性和不可感知性。
With widely disseminating of network audio document and the serious situation in the information security field, the audio steganography have been under more and more attention. This paper analyzes and summarized the current research status and existing problems of the audio steganography, then the major focus is around ensuring imperceptibility and robustness to enhance the capacity of hidden information embedded, and designs two kind of audio steganography algorithm in wavelet domain.
Firstly, according to the problem that some embeding methods such as plusing directly, quantization coding, modifing the energy ratio and so on are difficult to enhancing the embeding capacity, so the matrix coding is introducted. This method's characteristic is capable of greatly improving the embeding efficiency, so as to achieve the purpose of raising the embeding capacity. And the matrix coding help to reduce the proportion of the original audio changes, thereby reducing the effects of the original audio carrier'imperceptibility when embeded datas. In order to improve the problems as large calculation amount and slow execution speed of the traditional generation wavelet, the algorithm chooses the lifting wavelet transform coefficients to embed datas. Considering ensuring absolute concealment of the secret speech, the algorithm uses MPEG I Audio Psychoacoustic model 1 to compute masking threshold, and controls the embedded frames by masking threshold.
Secondly, according to the previous embeding methods's problem of the difficult controling to the wavelet coefficient's floating point numbers caused by processing directly, the PCM quantization coding is introducted to quantify the every segment's mean value of wavelet coefficient to a binary sequence. This method can greatly reduce the quantization error, and have stronger robustness than traditional ordinary single-valued quantization. The algorithm still uses the matrix coding embeding method, but it's for every segment's mean value of wavelet coefficient. Section size set according to application needs, you can achieve the embedding capacity to improve. In order to induce the calculation amount, the algorithm uses the less complex time-frequency analysis of audio signals to select the embedded frame by looking for voiced frame, imperceptibility can also be guaranteed.
Through the experimental analysis, the two kinds of wavelet domain audio steganography algorithm presented in this paper have higher embeding capacity than the same kind of algorithms, and guarantee a good robustness and imperceptibility.
引文
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[2]王朔中,张新鹏,张开文.数字密写和密写分析.北京：清华大学出版社,2005.
[3]杨义先,钮心忻,数字水印理论与技术.北京：高等教育出版社,2006,3.
[4]Artz D. Digital steganography hiding data within data. IEEE Internet Computing, 2001,5(3):75-80.
[5]王炳锡,彭天强.信息隐藏技术.北京：国防工业出版社,2007.
[6]Pfitzman B. Information hiding terminology. First Information Hiding Workshop, 1996,347-350.
[7]杨义先.数字水印基础教程.北京：人们邮电出版社,2007.
[8]高庆.用于版权保护的音频数字水印算法研究：[武汉理工大学硕士学位论文].武汉：武汉理工大学信息工程学院,2008,1-2.
[9]Bender W, et al. Techniques for data hiding. IBM Systems Journal.1996,35(3): 313-336.
[10]Boney L, Tewfik A, Hamdy K. Digital watermarks for audio signals. IEEE Int. Conf. on Multimedia Computing and Systems.1996, (1):473-480.
[11]N. Cvejic, T. Seppanen. Increasing robustness of LSB audio steganography using a novel embedding method. In Proc. IEEE Int. Conf. Info. Tech:Coding and Computing,2004, (2):533-537.
[12]N.Cvejic, T.Seppanen. Channel capacity of high bit rate audio data hiding algorithms in diverse transform domain. Proceeding of 2004 IEEE International Symposium on Communications and Information Technology,2004, (1):84-88.
[13]刘秀娟,郭立,邱天.改进的大容量多分辨率LSB音频隐写算法.计算机工程与应用,2006,42(30)：23-25.
[14]Byeong-Seob Ko, Ryouichi Nishimura, Yoiti Suzuki. Time-spread echo method for digital audio watermarking. IEEE Transactions on Multimedia.2005, 7(2):212-221.
[15]王慧琴.一种自适应音频数字水印算法的研究与仿真.系统仿真学报,2007,19(2)：461-464.
[16]A.Delforouzi, M.Pooyan. Increasing payload of echo hiding scheme using dual backward and forward delay kernels. Proceeding of 2007 IEEE International Symposium on Signal Processing and Information Technology.15-18 Dec. 2007:375-378.
[17]He X, Alexander I, Michael S. A high capacity watermarking technique for stereo audio. IEEE International Conference on Acoustics, Speech, and Signal Processing,2004,393-396.
[18]同鸣,郝重阳等.一种基于固定附加相位修正的音频信息隐藏方法.计算机工程,2006,32(1)：213-214.
[19]同鸣,姬红兵等.基于相位编码的音频信息隐藏方法.计算机工程,2008,34(9)：7-9.
[20]同鸣,刘晓军等.一种自适应的音频信息隐藏算法.计算机应用研究.2005：120-122.
[21]Hosei Matsuoka. Spread spectrum audio steganography using sub-band phase shifting. Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing. IEEE computer society, Washington, DC, USA,2006,3-6.
[22]范铁生,陆云山等.基于扩频系数的音频数字水印的回声方法.计算机应用,2006.6,26：173-174.
[23]Xiang S J, Huang J W, Yang R. Time-scale invariant audio watermarking based on the statistical features in time domain. The 8th Information Hiding Workshop, Old Town Alexandria, USA,2006,93-108.
[24]Ercelebi E, Subasi A. Robust multi bit and high quality audio watermarking using pseudo-random sequences. Computers & Electrical Engineering,2005, 31(8):525-536.
[25]谢玲,张家树,和红杰.一种基于非均匀离散傅立叶变换的鲁棒音频水印算法.计算机学报,2006,29(9)：1711-1721.
[26]范安东,孙琦.同时计算实序列的DFT和IDFT的新公式及其在数字音频水印中的应用.四川大学学报,2008,40(2)：96-100.
[27]马翼平,韩纪庆.DCT域音频水印：嵌入对策和算法.电子学报,2006,34(7)：1260-1264.
[28]温泉,王树勋,年桂君.DCT域音频水印：水印算法和不可感知性测度.电子学报,2007,35(9)：1702-1705.
[29]肖俊,王颖.基于多级离散余弦变换的鲁棒数字水印算法.计算机学报,2009,32(5)：1055-1061.
[30]马翼平,韩纪庆.基于能量特性分块的DCT域自适应音频水印算法.信号处 理,2006,22(4)：519-522.
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