小波变换在网络信息安全中的应用研究
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摘要
随着计算机技术和网络多媒体技术的广泛应用和发展，人们对计算机的依赖性越来越高，国际互联网也已成为知识经济时代重要传播途径之一。多媒体信息极大地丰富了计算机信息的表现能力，已经成为计算机信息中的一个重要部分，因此对多媒体信息的安全保密工作变得越来越重要。多媒体信息具有信息量大及易复制的特点，因此早期的加、解密算法在多媒体信息的安全保密方面已经显得力不从心。于是，数字世界里便出现了多种能够保护多媒体信息安全的新技术。信息隐藏便是这样一种技术。
小波分析是一种有效的分析工具，已经引起了各领域、各学科的科学家和研究人员的高度重视并取得了显著成绩。以小波分析为工具进行数字图像处理已经是小波研究与应用的热点之一。
本文首先简述了小波发展历史和小波的基本理论知识后，接着介绍了信息隐藏技术的概念及应用，并以小波为工具对数字图像处理进行了有益的探索。利用小波变换的多分辨率特性并结合人眼的视觉特性来进行图像的小波域分解，这样可以获得更好的图像保真度并且比在空域中的隐藏信息嵌入算法更稳健。针对待隐藏文件为图像的情况，由于直接按待隐藏图像的扫描顺序将其嵌入原始图像中时，在嵌入信息后的图像经过图像处理后会对提取信息的质量影响比较大，因此本文提出了一种隐藏算法，考虑在嵌入信息之前对待隐藏图像进行预处理，将待隐藏图像进行置乱。采用面包师变换的方法对图像进行置乱，以求得到更好的提取图像。实验结果表明，采用本文提出的算法，可以得到不可见性与鲁棒性较好的隐藏图像。本文为可执行文件与文本文件及其他各种格式的文件提供了一种通用的小波域隐藏方式，采用整数小波变换对原始图像进行处理，实验结果表明，可以达到较好的不可见性。
With the wide application and the fast development of the computer and multimedia, people depend more on the computer. And the Internet has been an important spread means of the knowledge and economy time. The multimedia enrich the behaving of computer information, and it has become a signify part of the computer information. So how to protect the safe of the multimedia is eager. The multimedia usually contains more information and it is copied easily, so it is difficult that we protect the safe of the multimedia through encryption and its converse arithmetic. Just so, there are some new kinds of technology can protect the safe of the
i
multimedia in the digital world. Information Hiding is one of them.
Wavelet is a useful analysis tool. It has gotten notable success. More and more scientists and investigators pay attention to wavelet in all kinds of fields and subjects. The digital image process on wavelet has been a hotspot in the study and application of wavelet.
This thesis describes the development history and the basis theory of wavelet briefly. Then we introduce the conception and application of information hiding. And we explore the digital image process with wavelet. With the multi-resolution analysis of wavelet and the vision character of the human eyes we decompose the image in
wavelet domain, which can get better image and is more robust than the arithmetic embedded with hid information in airspace. When the hid file is a image, common image process will affect the attracted information if we hide the hid image into the original image by its own scan order. So we scramble the hid image before it is embedded to the original image. Here we use the baker transposition to scramble the hid information to get better attracted image. The experiment result indicates it can get a invisible hid image and it is also robust through our arithmetic. With the integer wavelet transform to the original image we apply a general hid means in wavelet domain for all kinds of files especially for the executable files and text files. The result shows that we can get an invisible image.
小波分析是一种有效的分析工具，已经引起了各领域、各学科的科学家和研究人员的高度重视并取得了显著成绩。以小波分析为工具进行数字图像处理已经是小波研究与应用的热点之一。
本文首先简述了小波发展历史和小波的基本理论知识后，接着介绍了信息隐藏技术的概念及应用，并以小波为工具对数字图像处理进行了有益的探索。利用小波变换的多分辨率特性并结合人眼的视觉特性来进行图像的小波域分解，这样可以获得更好的图像保真度并且比在空域中的隐藏信息嵌入算法更稳健。针对待隐藏文件为图像的情况，由于直接按待隐藏图像的扫描顺序将其嵌入原始图像中时，在嵌入信息后的图像经过图像处理后会对提取信息的质量影响比较大，因此本文提出了一种隐藏算法，考虑在嵌入信息之前对待隐藏图像进行预处理，将待隐藏图像进行置乱。采用面包师变换的方法对图像进行置乱，以求得到更好的提取图像。实验结果表明，采用本文提出的算法，可以得到不可见性与鲁棒性较好的隐藏图像。本文为可执行文件与文本文件及其他各种格式的文件提供了一种通用的小波域隐藏方式，采用整数小波变换对原始图像进行处理，实验结果表明，可以达到较好的不可见性。
With the wide application and the fast development of the computer and multimedia, people depend more on the computer. And the Internet has been an important spread means of the knowledge and economy time. The multimedia enrich the behaving of computer information, and it has become a signify part of the computer information. So how to protect the safe of the multimedia is eager. The multimedia usually contains more information and it is copied easily, so it is difficult that we protect the safe of the multimedia through encryption and its converse arithmetic. Just so, there are some new kinds of technology can protect the safe of the
i
multimedia in the digital world. Information Hiding is one of them.
Wavelet is a useful analysis tool. It has gotten notable success. More and more scientists and investigators pay attention to wavelet in all kinds of fields and subjects. The digital image process on wavelet has been a hotspot in the study and application of wavelet.
This thesis describes the development history and the basis theory of wavelet briefly. Then we introduce the conception and application of information hiding. And we explore the digital image process with wavelet. With the multi-resolution analysis of wavelet and the vision character of the human eyes we decompose the image in
wavelet domain, which can get better image and is more robust than the arithmetic embedded with hid information in airspace. When the hid file is a image, common image process will affect the attracted information if we hide the hid image into the original image by its own scan order. So we scramble the hid image before it is embedded to the original image. Here we use the baker transposition to scramble the hid information to get better attracted image. The experiment result indicates it can get a invisible hid image and it is also robust through our arithmetic. With the integer wavelet transform to the original image we apply a general hid means in wavelet domain for all kinds of files especially for the executable files and text files. The result shows that we can get an invisible image.
引文
[1] 吴世忠、祝世雄等 译。应用密码学：协议、算法与C源程序，机械工业出版社，2000
[2] 孙伟平。猫与耗子的游戏——网络犯罪及其治理，北京出版社，1999
[3] Bruce Schneier, Applied Crytography: Protocols, Algorithms, and Source Code in C.,John Wiley & Sons,Inc., 1996
[4] Man Young Rhce,Cryptography and Secure Communications,McGraw-Hill Book Co., 1994
[5] Neal Koblitz,A Course in Number and Theory and Cryptography, Springer-Verlag, 世界图书出版公司, 1994
[6] 沈世镒。近代密码学，广西师范大学出版社，1998
[7] 王育民、何大可。保密学——基础与应用，西安电子科技大学出版社，1990
[8] 卢开澄。计算机密码学——计算机网络中的数据保密与安全，清华大学出版社，1998
[9] Arto Salomaa著，丁存生、单炜娟 译。公钥密码学，国防工业出版社，1999
[10] 王道顺。数字图像可视隐藏、加密和水印技术的若干理论问题及其应用(四川大学博士论文)，四川大学，2001
[11] Daubechies I. Orthonormal bases of compactly supported wavelets. Comm. Pure Appl. Math, 1988, 41: 909-996
[12] Daubechies I. Ten Lectures on Wavelets. CBMS Conference Series in Applied Mathematics, SIAM, Philadelphia, 1992
[13] Alkin O. and Caglar H. Design of efficient M-band coder with linear-phase and perfect reconstruction properties. IEEE Trans. Signal Processing, 1995, 45(7): 1579-1290
[14] Steffen P., Heller P.N. and et al. Theory of regular M-band wavelet bases. IEEE Trans. Signal Processing, 1993, 41(12): 3497-3510
[15] Bi N., Dai X.X. and Sun Q.Y. Construction 9f compactly supported M-band wavelets. Appl. Comput. Harmon. Anal., 1999, 6:113-131
[16] Mallat S. A Theory for multiresolution signal, al decomposition: the wavelet representation. IEEE Trans. On PAMI, 1989.7,11(7): 674-693
[17] Mallat S. Multiresolution approximations and wavelet orthonormal bases of L~2 (R). Trans. Amer. Math. Soc., 1989.9, 315:69-87
[18] Mallat S. Multifrequency channel decomposition of images and wavelets. IEEE Trans. ASSP., 1989. 12, 37:2091-2110
[19] Mallat S. A Wavelet Tour of Signal Processing. London: Academic Press, 1998
[20] 李兵兵等。小波基的构造及算法设计，电子科学学刊，1994，16(6)：P646-650
[21] 李世雄。小波变换及其应用，高等教育出版社，1997
[22] Cohen A, Daubechies I. And Feauveau J.C. Biorthogonal bases of compactly supported wavelets. Common. Pure Appl. Math, 1992.5, 45(5): 485-560
[23] Chui C.K. An introduction to wavelets. Academic Press, Inc., 1992
[24] Chui C.K. Wavelets: A Tutorial in Theory and Application. Academic Press, San Diego, CA, 1992
[25] Chui C.K., Stockler J. and Ward J.D. Compactly supported box-spline wavelets. Approx. Theory Appl., 1992, 8(3): 77-100
[26] Coifman R. R. and Wickerhauser M. V. Entropy based algorithms for best basis selection. IEEE Trans. Inform. Theory, 1992.2, 38(2): 713-718
[27] Ramchandran K. and Vetterli M. Best wavelet packet bases in a rate-distortion sence. IEEE Trans. IP. 1993.4, 2:160-175
[28] Coifman R. R. and Wickerhauser M. V. Adapted waveform analysis as a tool for modeling, feature extraction and denoting. Optical Engineering, 1994.7, 33(7):2170-2174
[29] Goodman T. N. T., Lee S. L. and Tang W. S. Wavelet wandering subspaces. Trans. Amer. Math. Soc, 1993.8, 338(2):639-654
[30] Goodman T. N. T. and Lee S. L. Wavelets of multiplicity r. Trans. Amer. Math. Soc., 1994.3, 342(1):307-324
[31] Geronimo J.S., Hardin D.P., and Massopust P.R. Fractal functions and wavelet expansions based on several scaling functions. J. Approx. Theory, 1994, 78(3): 373-401
[32] Donovan G., Geronimo J. S., Hardin D. and Massopust P. Construction of orthogonal wavelets using fractal interpolation function. SIAM J. Math. Anal., 1996,27:1158-1192
[33] Shensa M. J. The discrete wavelet transform: wedding a trous and Mallat algorithm. IEEE Trans. SP., 1992.10, 40(10): 2464-2483
[34] Walter G. G. A sampling theorem for wavelet subspace. IEEE Trans. Inform. Theory, 1992. 3, 38(2): 881-884
[35] Donoho D. L. Interpolating wavelet transform. Technical report, Dept. of Statistics Stanford Univ., 1992. 10
[36] 陈明奇，钮心忻，杨义先。基于小波变换及矢量量化的隐像术，计算机研究与发展，2001年02期
[37] 丁玮。数字图像信息安全的算法研究[中国科学院博士论文]，中国科学院计算技术研究所，2000
[38] 钱思进。信息隐藏与信息安全，第二届全国信息隐藏学术研讨会论文集，北京：2000年6月，PP．136-138
[39] 王文惠，孟兵，周良柱。信息时代的隐写术，第二届全国信息隐藏学术研讨会论文集，北京：2000年6月，pp．60-63
[40] Fabien A. P. Petitcolas, Ross J. Anderson, Markus G. Kuhn, "Information hiding-a survey." Proceedings of the IEEE, Vol. 87, No. 7, pp: 1062-1078, July 1999
[41] J. Reeds, "Solved: the ciphers in book Ⅲ of trithemius' steganographia," Cryptologia, vol.ⅩⅫ, no. 4, pp.291-317, Oct. 1998
[42] Baranousky A, Daems D. Design of one-dimensional chaotic maps with prescribed statistical properties. International Journal of Bifurcation and Chaos, 1995, 5 (6) : 1585-1598
[43] 吴晓涵。面向对象结构分析程序设计，科学出版社，北京：2002
[2] 孙伟平。猫与耗子的游戏——网络犯罪及其治理，北京出版社，1999
[3] Bruce Schneier, Applied Crytography: Protocols, Algorithms, and Source Code in C.,John Wiley & Sons,Inc., 1996
[4] Man Young Rhce,Cryptography and Secure Communications,McGraw-Hill Book Co., 1994
[5] Neal Koblitz,A Course in Number and Theory and Cryptography, Springer-Verlag, 世界图书出版公司, 1994
[6] 沈世镒。近代密码学，广西师范大学出版社，1998
[7] 王育民、何大可。保密学——基础与应用，西安电子科技大学出版社，1990
[8] 卢开澄。计算机密码学——计算机网络中的数据保密与安全，清华大学出版社，1998
[9] Arto Salomaa著，丁存生、单炜娟 译。公钥密码学，国防工业出版社，1999
[10] 王道顺。数字图像可视隐藏、加密和水印技术的若干理论问题及其应用(四川大学博士论文)，四川大学，2001
[11] Daubechies I. Orthonormal bases of compactly supported wavelets. Comm. Pure Appl. Math, 1988, 41: 909-996
[12] Daubechies I. Ten Lectures on Wavelets. CBMS Conference Series in Applied Mathematics, SIAM, Philadelphia, 1992
[13] Alkin O. and Caglar H. Design of efficient M-band coder with linear-phase and perfect reconstruction properties. IEEE Trans. Signal Processing, 1995, 45(7): 1579-1290
[14] Steffen P., Heller P.N. and et al. Theory of regular M-band wavelet bases. IEEE Trans. Signal Processing, 1993, 41(12): 3497-3510
[15] Bi N., Dai X.X. and Sun Q.Y. Construction 9f compactly supported M-band wavelets. Appl. Comput. Harmon. Anal., 1999, 6:113-131
[16] Mallat S. A Theory for multiresolution signal, al decomposition: the wavelet representation. IEEE Trans. On PAMI, 1989.7,11(7): 674-693
[17] Mallat S. Multiresolution approximations and wavelet orthonormal bases of L~2 (R). Trans. Amer. Math. Soc., 1989.9, 315:69-87
[18] Mallat S. Multifrequency channel decomposition of images and wavelets. IEEE Trans. ASSP., 1989. 12, 37:2091-2110
[19] Mallat S. A Wavelet Tour of Signal Processing. London: Academic Press, 1998
[20] 李兵兵等。小波基的构造及算法设计，电子科学学刊，1994，16(6)：P646-650
[21] 李世雄。小波变换及其应用，高等教育出版社，1997
[22] Cohen A, Daubechies I. And Feauveau J.C. Biorthogonal bases of compactly supported wavelets. Common. Pure Appl. Math, 1992.5, 45(5): 485-560
[23] Chui C.K. An introduction to wavelets. Academic Press, Inc., 1992
[24] Chui C.K. Wavelets: A Tutorial in Theory and Application. Academic Press, San Diego, CA, 1992
[25] Chui C.K., Stockler J. and Ward J.D. Compactly supported box-spline wavelets. Approx. Theory Appl., 1992, 8(3): 77-100
[26] Coifman R. R. and Wickerhauser M. V. Entropy based algorithms for best basis selection. IEEE Trans. Inform. Theory, 1992.2, 38(2): 713-718
[27] Ramchandran K. and Vetterli M. Best wavelet packet bases in a rate-distortion sence. IEEE Trans. IP. 1993.4, 2:160-175
[28] Coifman R. R. and Wickerhauser M. V. Adapted waveform analysis as a tool for modeling, feature extraction and denoting. Optical Engineering, 1994.7, 33(7):2170-2174
[29] Goodman T. N. T., Lee S. L. and Tang W. S. Wavelet wandering subspaces. Trans. Amer. Math. Soc, 1993.8, 338(2):639-654
[30] Goodman T. N. T. and Lee S. L. Wavelets of multiplicity r. Trans. Amer. Math. Soc., 1994.3, 342(1):307-324
[31] Geronimo J.S., Hardin D.P., and Massopust P.R. Fractal functions and wavelet expansions based on several scaling functions. J. Approx. Theory, 1994, 78(3): 373-401
[32] Donovan G., Geronimo J. S., Hardin D. and Massopust P. Construction of orthogonal wavelets using fractal interpolation function. SIAM J. Math. Anal., 1996,27:1158-1192
[33] Shensa M. J. The discrete wavelet transform: wedding a trous and Mallat algorithm. IEEE Trans. SP., 1992.10, 40(10): 2464-2483
[34] Walter G. G. A sampling theorem for wavelet subspace. IEEE Trans. Inform. Theory, 1992. 3, 38(2): 881-884
[35] Donoho D. L. Interpolating wavelet transform. Technical report, Dept. of Statistics Stanford Univ., 1992. 10
[36] 陈明奇，钮心忻，杨义先。基于小波变换及矢量量化的隐像术，计算机研究与发展，2001年02期
[37] 丁玮。数字图像信息安全的算法研究[中国科学院博士论文]，中国科学院计算技术研究所，2000
[38] 钱思进。信息隐藏与信息安全，第二届全国信息隐藏学术研讨会论文集，北京：2000年6月，PP．136-138
[39] 王文惠，孟兵，周良柱。信息时代的隐写术，第二届全国信息隐藏学术研讨会论文集，北京：2000年6月，pp．60-63
[40] Fabien A. P. Petitcolas, Ross J. Anderson, Markus G. Kuhn, "Information hiding-a survey." Proceedings of the IEEE, Vol. 87, No. 7, pp: 1062-1078, July 1999
[41] J. Reeds, "Solved: the ciphers in book Ⅲ of trithemius' steganographia," Cryptologia, vol.ⅩⅫ, no. 4, pp.291-317, Oct. 1998
[42] Baranousky A, Daems D. Design of one-dimensional chaotic maps with prescribed statistical properties. International Journal of Bifurcation and Chaos, 1995, 5 (6) : 1585-1598
[43] 吴晓涵。面向对象结构分析程序设计，科学出版社，北京：2002