基于盲源分离的图像与语音加密新方法研究
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摘要
在社会信息化的进程中,信息已成为社会发展的重要资源,而Internet技术的飞速发展,又使信息的网上传播变得极其迅速和方便。然而,由于Internet具有全球性和开放性,任何人都可以自由地接入,这给信息安全带来了巨大隐患。与此同时,多媒体技术持续迅猛发展,又将图像和语音信息的安全问题提到了新的高度。因此,图像与语音的数据安全已成为一个全球性的研究课题。
通常,可以采用常规的数据加密方法对图像与语音信息进行加密。为了进一步提高保密强度,增强安全性,需要利用一些新理论与新方法来探索图像与语音加密的新方案。盲源分离(Blind Source Separation,BSS)是统计信号处理的一个活跃分支,它能在各源信号和传输通道参数(混合矩阵)均未知的情况下,仅仅利用源信号的多个观测(混合)信号,去恢复各源信号。盲源分离的特有优势在于对先验知识要求极低,因此很快成为信号处理领域的一个研究热点。大量的研究论文展示了国内外学者在盲源分离理论与应用方面取得的丰硕成果。然而,截至目前,国内外对盲源分离的应用研究大多集中在无线通信、生物医学和地震勘探等诸多领域,极少有文献报道其在数据加密方面的应用。
本文深入研究了基于盲源分离理论进行图像与语音加密的可行性。在此基础上,借鉴密码学上应用数学难题设计加密算法的思想,利用盲源分离理论的欠定难题及其易于具备一次一密加密方案密钥特性的优势,系统提出了图像和语音的盲源分离加密新方法。理论分析和仿真结果都表明,若密钥信号的随机性好,该方法可近似达到无条件安全的高保密强度。
本文取得的主要研究成果如下:
(1) 在深入研究盲源分离理论和密码学的基础上,利用盲源分离理论的欠定难题,全面系统地构建了盲源分离图像加密新方法。为了使该方法真正具备一次一密加密方案随机不重复的优秀密钥特性,同时满足盲源分离要求,本文给出了生成密钥信号的统计独立和非高斯性两个必要条件,阐明了其必要性。为了确保无密钥时盲源分离欠定难题的难解性,应用Cao和Liu提出的L行可分解定理(L-row decomposable theorem),构造了两种形式的欠定加密混合矩阵,证明了其不可分离性。
(2) 通过应用明文语音的波形信息,基于盲源分离理论有效地建立了语音加密新方法。语音加密时逐帧进行,并且一帧语音需等分成多段进行欠定混合加密,所以盲源分离的不确定性可能导致各解密语音段与各原始语音段之间存在顺序、幅度和相位差异。考虑到盲源分离的不确定性源于源信号先验知识的缺乏,本文通过记录和利用原始语音段的过零率、波形最大值和最小值等部分先验信息,有效消除了盲源分离解密语音的顺
With the developement of information society, information has become the most important and valuable resources to be transmitted conveniently and promptly through Internet. However, the globality and openness of Internet severely threaten the information security. At the same time, image and speech communications become more and more widely used as the multimedia technology is progressing rapidly. Therefore, the security of images and speeches has become a worldwide problem.Usually, regular data encryption methods can be used to encrypt images and speeches. To further enhance their security level, new theories and new methods need to be explored to give new schemes for encrypting images and speeches. Blind source separation (BSS) is one active branch of stochastic signal processing. It can recover source signals from their observed mixtures without knowing the source signals and the mixing coefficients. BSS has received considerable attention in recent years, and has been applied to many fields such as wireless communications, biomedical engineering. However, there have been only a few reports for its application to signal encryption thus far.Motivated by the fact that the security of many cryptosystems relies on the apparent intractability of the computational problem such as the integer factorization problem, this dissertation explores the feasibility of BSS-based signal encryption, and exploits the intractability of the underdetermined BSS problem to present novel encryption methods for encrypting images and speeches. The BSS-based encryption method can have the perfect key characteristics of one-time pads cipher, which is unconditionally secure. If the key signals pseudorandomly generated are completely random, the proposed method is approximately unconditionally secure. Extensive computer simulations and performance analyses demonstrate the efficiency of the BSS-based encryption.The main contributions of this dissertation are as follows:(1) By studying the BSS theory and the cryptography, the underdetermined BSS problem has been totally exploited to establish a novel method for encrypting images with high security. Two necessary conditions for generating the key signals are given based on BSS theory and the key characteristics of one-time pads cipher, and their necessity is shown. Two mixing matrixes for underdetermined encryption are constructed by using the L-row decomposable theorem, and their inseparability is also proved.
(2) By using some waveform information about the original speech, a novel method for encrypting speeches is proposed based on BSS. The proposed method encrypts the original speech frame by frame, and each frame is divided into multiple segments for underdetermined mixing encryption. Due to the indeterminacy of BSS, the BSS decrypted segments may have permutation and scale ambiguities compared with the original segments. Considering that the BSS indeterminacy is caused by lack of prior information about sources, the numbers of zero-crossings, the maximum and the minimum of each original segmen are recorded and used to eliminate ambiguity of the BSS decrypted speech in permutation and amplitude. As a result, the decrypted speech signal has been recovered with very high quality.(3) Since the computational load of the BSS algorithms usually has nonlinear relation (e.g., square, cubic, etc) with the number of the source signals, a fast method for decrypting images is given by using the knowledge of the key images on the receiving side, and by employing the technique of adaptive noise cancellation to half reduce the number of the source signals for the BSS decryption. Besides, strongly correlated images are well decrypted with the existing ICA algorithms by decorrelation of the encrypted images before BSS.(4) Based on the masking technique, image cryptosystems with dual encryption are established by using BSS to add another encryption level, which includes "specific mixing" and "BSS", besides the existing encryption methods.(5) Several different BSS adaptive algorithms are unified to one form with various nonlinear functions through reasonable derivation and conversion. The stability criterion for choosing nonlinear function in the unified form is described. The combined criterion for choosing the nonlinear function that gives attention to several desired performances such as separation performance, robustness and convergence speed is given.In summary, this dissertation proposes a novel application of BSS to image encryption and speech encryption. The BSS-based encryption methods can be largely used for secure transmission of images and speeches through Internet.
通常,可以采用常规的数据加密方法对图像与语音信息进行加密。为了进一步提高保密强度,增强安全性,需要利用一些新理论与新方法来探索图像与语音加密的新方案。盲源分离(Blind Source Separation,BSS)是统计信号处理的一个活跃分支,它能在各源信号和传输通道参数(混合矩阵)均未知的情况下,仅仅利用源信号的多个观测(混合)信号,去恢复各源信号。盲源分离的特有优势在于对先验知识要求极低,因此很快成为信号处理领域的一个研究热点。大量的研究论文展示了国内外学者在盲源分离理论与应用方面取得的丰硕成果。然而,截至目前,国内外对盲源分离的应用研究大多集中在无线通信、生物医学和地震勘探等诸多领域,极少有文献报道其在数据加密方面的应用。
本文深入研究了基于盲源分离理论进行图像与语音加密的可行性。在此基础上,借鉴密码学上应用数学难题设计加密算法的思想,利用盲源分离理论的欠定难题及其易于具备一次一密加密方案密钥特性的优势,系统提出了图像和语音的盲源分离加密新方法。理论分析和仿真结果都表明,若密钥信号的随机性好,该方法可近似达到无条件安全的高保密强度。
本文取得的主要研究成果如下:
(1) 在深入研究盲源分离理论和密码学的基础上,利用盲源分离理论的欠定难题,全面系统地构建了盲源分离图像加密新方法。为了使该方法真正具备一次一密加密方案随机不重复的优秀密钥特性,同时满足盲源分离要求,本文给出了生成密钥信号的统计独立和非高斯性两个必要条件,阐明了其必要性。为了确保无密钥时盲源分离欠定难题的难解性,应用Cao和Liu提出的L行可分解定理(L-row decomposable theorem),构造了两种形式的欠定加密混合矩阵,证明了其不可分离性。
(2) 通过应用明文语音的波形信息,基于盲源分离理论有效地建立了语音加密新方法。语音加密时逐帧进行,并且一帧语音需等分成多段进行欠定混合加密,所以盲源分离的不确定性可能导致各解密语音段与各原始语音段之间存在顺序、幅度和相位差异。考虑到盲源分离的不确定性源于源信号先验知识的缺乏,本文通过记录和利用原始语音段的过零率、波形最大值和最小值等部分先验信息,有效消除了盲源分离解密语音的顺
With the developement of information society, information has become the most important and valuable resources to be transmitted conveniently and promptly through Internet. However, the globality and openness of Internet severely threaten the information security. At the same time, image and speech communications become more and more widely used as the multimedia technology is progressing rapidly. Therefore, the security of images and speeches has become a worldwide problem.Usually, regular data encryption methods can be used to encrypt images and speeches. To further enhance their security level, new theories and new methods need to be explored to give new schemes for encrypting images and speeches. Blind source separation (BSS) is one active branch of stochastic signal processing. It can recover source signals from their observed mixtures without knowing the source signals and the mixing coefficients. BSS has received considerable attention in recent years, and has been applied to many fields such as wireless communications, biomedical engineering. However, there have been only a few reports for its application to signal encryption thus far.Motivated by the fact that the security of many cryptosystems relies on the apparent intractability of the computational problem such as the integer factorization problem, this dissertation explores the feasibility of BSS-based signal encryption, and exploits the intractability of the underdetermined BSS problem to present novel encryption methods for encrypting images and speeches. The BSS-based encryption method can have the perfect key characteristics of one-time pads cipher, which is unconditionally secure. If the key signals pseudorandomly generated are completely random, the proposed method is approximately unconditionally secure. Extensive computer simulations and performance analyses demonstrate the efficiency of the BSS-based encryption.The main contributions of this dissertation are as follows:(1) By studying the BSS theory and the cryptography, the underdetermined BSS problem has been totally exploited to establish a novel method for encrypting images with high security. Two necessary conditions for generating the key signals are given based on BSS theory and the key characteristics of one-time pads cipher, and their necessity is shown. Two mixing matrixes for underdetermined encryption are constructed by using the L-row decomposable theorem, and their inseparability is also proved.
(2) By using some waveform information about the original speech, a novel method for encrypting speeches is proposed based on BSS. The proposed method encrypts the original speech frame by frame, and each frame is divided into multiple segments for underdetermined mixing encryption. Due to the indeterminacy of BSS, the BSS decrypted segments may have permutation and scale ambiguities compared with the original segments. Considering that the BSS indeterminacy is caused by lack of prior information about sources, the numbers of zero-crossings, the maximum and the minimum of each original segmen are recorded and used to eliminate ambiguity of the BSS decrypted speech in permutation and amplitude. As a result, the decrypted speech signal has been recovered with very high quality.(3) Since the computational load of the BSS algorithms usually has nonlinear relation (e.g., square, cubic, etc) with the number of the source signals, a fast method for decrypting images is given by using the knowledge of the key images on the receiving side, and by employing the technique of adaptive noise cancellation to half reduce the number of the source signals for the BSS decryption. Besides, strongly correlated images are well decrypted with the existing ICA algorithms by decorrelation of the encrypted images before BSS.(4) Based on the masking technique, image cryptosystems with dual encryption are established by using BSS to add another encryption level, which includes "specific mixing" and "BSS", besides the existing encryption methods.(5) Several different BSS adaptive algorithms are unified to one form with various nonlinear functions through reasonable derivation and conversion. The stability criterion for choosing nonlinear function in the unified form is described. The combined criterion for choosing the nonlinear function that gives attention to several desired performances such as separation performance, robustness and convergence speed is given.In summary, this dissertation proposes a novel application of BSS to image encryption and speech encryption. The BSS-based encryption methods can be largely used for secure transmission of images and speeches through Internet.
引文
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