数字图像与语音被动取证技术研究
|
摘要
网络带宽的增加和数字压缩算法的发展使得数字多媒体(视频、音频、图像等)成为了最佳的信息共享和交流的媒介。此外,个人电脑的普及和多媒体编辑软件的广泛应用,使得对多媒体数据地编辑、修改和伪造变得越加容易。恶意的攻击者可以轻易地对多媒体数据进行篡改与伪造,以达到恶意的目的。近年来,频繁出现的多媒体数据伪造事件,使公众对多媒体数据的完整性、可靠性和真实性提出了质疑,多媒体数据的取证成为当前国际信息安全领域研究的热点。
针对保障多媒体信息的完整性、可靠性和真实性的需求,结合科研项目的研究需要,本文致力于对数字多媒体被动取证的研究,分别以图像和语音为对象,研究了图像隐写与隐写分析技术和语音取证技术。
针对当前可逆信息隐藏算法缺乏安全性分析的现状,首先分析了当前流行的三种可逆信息隐藏算法,指出信息嵌入过程中引入的失真特性。理论研究发现,嵌入失真主要存在于图像水平方向的差分直方图中,而垂直方向的差分直方图基本保持不变。然后分别利用拉普拉斯模型、高斯模型以及相邻像素模型来描述差分直方图的分布特性,并同时提出利用水平和垂直方向差分直方图的相似度作为特征,实现了对常见的几种可逆信息隐藏算法地有效检测。实验表明,基于水平和垂直方向差分直方图相似度模型的检测算法的性能优于拉普拉斯模型、高斯模型和相邻像素模型。
针对目前对调色板图像的通用隐写分析研究较少的现状,提出了一种基于广义差值直方图和颜色相关图的调色板图像通用隐写算法。该方案首先提出了调色板图像隐写的通用框架,并从理论上分析了信息隐藏对调色板图像像素之间相关性的影响。提出利用RGB颜色各通道的广义差分直方图和颜色相关图来描述像素间的相关性,并提取差值直方图的特征函数矩、颜色相关图的特征函数重心以及高阶中心距作为特征,利用支持向量机作为分类器,实现了对几种常见GIF调色板图像隐写算法和隐写软件的可靠检测。实验结果表明,该算法的性能优于Lyu等人的通用检测算法和Du的专用检测算法,并与Fridrich的专用检测算法性能相当,但更具有推广能力。
提出了一种利用语音回声和背景噪声特征的录音环境识别算法。该算法认为,回声信号是一种环境相关的“固有指纹”,利用语音中的回声成分,可以实现录音环境地识别。该算法首先利用去回声算法,通过逆滤波的方式提取语音信号中的回声成分,然后利用粒子滤波提取语音信号的背景噪声作为补充,并提取MFCC、LMSC以及均值、方差、偏斜系数、峰度等高阶统计量作为分类特征,利用支持向量机实现对环境的分类检测。利用在8个不同环境中录制的2240段录音进行测试,结果表明,本方案提取的特征可以有效地区分录音环境,性能优于直接从语音信号中提取的特征,并且从回声信号中提取的特征不依赖于麦克风的类型。鲁棒性实验结果表明,该方案提取的特征对多种不同比特率的MP3压缩均具有鲁棒性。
Due to immense increase in data rate and development of novel data compression algorithms, digital multimedia (Video, Audio, Image etc) has become the best choice for information sharing. Growth in the usage of personal computer and multimedia software not only provides huge benefits to human race but also opens a back door for evil doers as it has become easy to edit, modify, tamper, and forge the multimedia data, according to the requirements of operator. This technology can be abused by malicious adversaries to generate the tampered or forgery copies for purposes such as pretending to be the owner of digital copy, removing/creating some objects in video, image etc. Recently, due to the spread of counterfeit, the integrity, reliability, and authenticity of multimedia data are the primary considerations of governments and as a result digital forensics has turned into one of the top research directions.
According to the requirements of the integrity, reliability, and authenticity of multimedia data, this thesis is devoted to the exploration of passive digital forensics, including digital image steganalysis and digital audio forensics.
Some pioneer research on the security analysis of reversible data hiding has been done in past, so three popular reversible data hiding methods were implemented. The statistical distortion introduced by data embedding was analyzed. Theoretical analysis illustrated that there was significant degradation in the horizontal component of statistical distribution of difference histogram. However, the vertical component of the statistical distribution of difference histogram was preserved. Quasi-Laplace Distribution (QLD), Generalized Gaussian distribution (GGD), and Adjacent Pixel Value (APV) model were introduced to describe the statistical distribution of difference histogram, separately. A simple and intuitive model, Horizontal and Vertical Difference Histogram (HVDH), which is based on similarity of horizontal and vertical difference histograms, was proposed to detect the presence of hidden message. Experimental results have shown that HVDH model can detect the presence of hidden information and it has outperformed QLD, GGD, and APV model too.
Factually, only few blind steganalysis schemes for GIF image are present today. A novel blind steganalysis for GIF image based on generalized difference histogram and color correlogram was proposed. In the beginning, we introduced the general framework for hiding data in GIF image and analyzed the statistical distortion between the pixels. The generalized difference histogram of each RGB channel and the color correlogram was explored to capture the correlation between pixels. Finally, the absolute moments of characteristic function, Absolute Center of Mass (ACOM) of the characteristic function and high-order absolute moments of probability density function were extracted from the generalized difference histograms and color correlogram. Experimental results illuminated that the proposed scheme can not only detect the presence of hidden message embedded by several current steganography methods but also outperform Lyn's blind steganalysis scheme, and Du's target steganalysis scheme. It has comparable performance with Fridrich's target steganalysis against steganography software EzStego. The proposed scheme has better capability of generalization as it is a blind steganalysis method.
An Acoustic Environment Identification (AEI) scheme based on reverberation and background noise was proposed. Reverberation was considered as a kind of "intrinsic fingerprint" of environment which is used to capture the trace of environment. The features extracted from reverberation can be used for AEI. Firstly, blind de-reverberation method using block-based inverse filtering was introduced to separate the dry signal and reverberation. In order to improve the performance, background noise was taken as complementary feature. Background noise was estimated through particle filtering. Secondly,128-dimension feature vector, consisting of30Mel-frequency Cepstral Coefficients (MFCC),30Logarithmic Mel-spectral Coefficients (LMSE), mean, variance, kurtosis and skewness from reverberation and background noise were extracted for effectiveness verification. Experimental results on more than2240audio clips recorded in8different environments showed that the proposed framework was able to differentiate different environments, and outperformed the features extracted from the audio without de-reverberation and background noise estimation. The microphone independent test clarified that the performance of proposed features is not influenced by the type of microphone used to record the training and testing audio files. It has illustrated that the reverberation features is robust to MP3compression with various bit rates.
针对保障多媒体信息的完整性、可靠性和真实性的需求,结合科研项目的研究需要,本文致力于对数字多媒体被动取证的研究,分别以图像和语音为对象,研究了图像隐写与隐写分析技术和语音取证技术。
针对当前可逆信息隐藏算法缺乏安全性分析的现状,首先分析了当前流行的三种可逆信息隐藏算法,指出信息嵌入过程中引入的失真特性。理论研究发现,嵌入失真主要存在于图像水平方向的差分直方图中,而垂直方向的差分直方图基本保持不变。然后分别利用拉普拉斯模型、高斯模型以及相邻像素模型来描述差分直方图的分布特性,并同时提出利用水平和垂直方向差分直方图的相似度作为特征,实现了对常见的几种可逆信息隐藏算法地有效检测。实验表明,基于水平和垂直方向差分直方图相似度模型的检测算法的性能优于拉普拉斯模型、高斯模型和相邻像素模型。
针对目前对调色板图像的通用隐写分析研究较少的现状,提出了一种基于广义差值直方图和颜色相关图的调色板图像通用隐写算法。该方案首先提出了调色板图像隐写的通用框架,并从理论上分析了信息隐藏对调色板图像像素之间相关性的影响。提出利用RGB颜色各通道的广义差分直方图和颜色相关图来描述像素间的相关性,并提取差值直方图的特征函数矩、颜色相关图的特征函数重心以及高阶中心距作为特征,利用支持向量机作为分类器,实现了对几种常见GIF调色板图像隐写算法和隐写软件的可靠检测。实验结果表明,该算法的性能优于Lyu等人的通用检测算法和Du的专用检测算法,并与Fridrich的专用检测算法性能相当,但更具有推广能力。
提出了一种利用语音回声和背景噪声特征的录音环境识别算法。该算法认为,回声信号是一种环境相关的“固有指纹”,利用语音中的回声成分,可以实现录音环境地识别。该算法首先利用去回声算法,通过逆滤波的方式提取语音信号中的回声成分,然后利用粒子滤波提取语音信号的背景噪声作为补充,并提取MFCC、LMSC以及均值、方差、偏斜系数、峰度等高阶统计量作为分类特征,利用支持向量机实现对环境的分类检测。利用在8个不同环境中录制的2240段录音进行测试,结果表明,本方案提取的特征可以有效地区分录音环境,性能优于直接从语音信号中提取的特征,并且从回声信号中提取的特征不依赖于麦克风的类型。鲁棒性实验结果表明,该方案提取的特征对多种不同比特率的MP3压缩均具有鲁棒性。
Due to immense increase in data rate and development of novel data compression algorithms, digital multimedia (Video, Audio, Image etc) has become the best choice for information sharing. Growth in the usage of personal computer and multimedia software not only provides huge benefits to human race but also opens a back door for evil doers as it has become easy to edit, modify, tamper, and forge the multimedia data, according to the requirements of operator. This technology can be abused by malicious adversaries to generate the tampered or forgery copies for purposes such as pretending to be the owner of digital copy, removing/creating some objects in video, image etc. Recently, due to the spread of counterfeit, the integrity, reliability, and authenticity of multimedia data are the primary considerations of governments and as a result digital forensics has turned into one of the top research directions.
According to the requirements of the integrity, reliability, and authenticity of multimedia data, this thesis is devoted to the exploration of passive digital forensics, including digital image steganalysis and digital audio forensics.
Some pioneer research on the security analysis of reversible data hiding has been done in past, so three popular reversible data hiding methods were implemented. The statistical distortion introduced by data embedding was analyzed. Theoretical analysis illustrated that there was significant degradation in the horizontal component of statistical distribution of difference histogram. However, the vertical component of the statistical distribution of difference histogram was preserved. Quasi-Laplace Distribution (QLD), Generalized Gaussian distribution (GGD), and Adjacent Pixel Value (APV) model were introduced to describe the statistical distribution of difference histogram, separately. A simple and intuitive model, Horizontal and Vertical Difference Histogram (HVDH), which is based on similarity of horizontal and vertical difference histograms, was proposed to detect the presence of hidden message. Experimental results have shown that HVDH model can detect the presence of hidden information and it has outperformed QLD, GGD, and APV model too.
Factually, only few blind steganalysis schemes for GIF image are present today. A novel blind steganalysis for GIF image based on generalized difference histogram and color correlogram was proposed. In the beginning, we introduced the general framework for hiding data in GIF image and analyzed the statistical distortion between the pixels. The generalized difference histogram of each RGB channel and the color correlogram was explored to capture the correlation between pixels. Finally, the absolute moments of characteristic function, Absolute Center of Mass (ACOM) of the characteristic function and high-order absolute moments of probability density function were extracted from the generalized difference histograms and color correlogram. Experimental results illuminated that the proposed scheme can not only detect the presence of hidden message embedded by several current steganography methods but also outperform Lyn's blind steganalysis scheme, and Du's target steganalysis scheme. It has comparable performance with Fridrich's target steganalysis against steganography software EzStego. The proposed scheme has better capability of generalization as it is a blind steganalysis method.
An Acoustic Environment Identification (AEI) scheme based on reverberation and background noise was proposed. Reverberation was considered as a kind of "intrinsic fingerprint" of environment which is used to capture the trace of environment. The features extracted from reverberation can be used for AEI. Firstly, blind de-reverberation method using block-based inverse filtering was introduced to separate the dry signal and reverberation. In order to improve the performance, background noise was taken as complementary feature. Background noise was estimated through particle filtering. Secondly,128-dimension feature vector, consisting of30Mel-frequency Cepstral Coefficients (MFCC),30Logarithmic Mel-spectral Coefficients (LMSE), mean, variance, kurtosis and skewness from reverberation and background noise were extracted for effectiveness verification. Experimental results on more than2240audio clips recorded in8different environments showed that the proposed framework was able to differentiate different environments, and outperformed the features extracted from the audio without de-reverberation and background noise estimation. The microphone independent test clarified that the performance of proposed features is not influenced by the type of microphone used to record the training and testing audio files. It has illustrated that the reverberation features is robust to MP3compression with various bit rates.
引文
[1]http://www.adobe.com.
[2]http://www.washingtonpost.com.
[3]R. C. Maher. Audio Forensic Examination:Authenticity, Enhancement, and Interpretation[J]. IEEE Signal Processing Magazine,2009,26(2):84-94.
[4]吴金海,林福宗.基于数字水印的图像认证技术[J].计算机学报,2004,27(9)：1153-1161.
[5]胡永健,刘琲贝,贺前华.数字多媒体取证技术综述[J].计算机应用,2010,30(3),657-661.
[6]Behrouz A. Forouzan,密码学与网络安全[M].马振晗,贾军保译,北京：清华大学出版社,2009.
[7]I. J. Cox, M. L.Miller, J. A. Bloom,数字水印[M].王颖,黄志蓓等译.北京：电子工业出版社,2003.
[8]http://www.cs.dartmouth.edu/farid/Hany_Farid/Home.html.
[9]T. T. Ng, S. F. Chang, C. Y. Lin. Passive Blind Image Forensics Multimedia Security Technologies for Digital Rights Management[M],2006:383-412.
[10]H. Farid. Creating and Detecting Doctored and Virtual Images:Implications to the Child Pornography Prevention Act [EB/OL]. Technical Report, Department of Computer Science, Dartmouth College, New Hampshire, USA,2004. http://www.ists.dartmouth.edu/library/100.pdf.
[11]陈海鹏.数字图像真伪鉴别技术研究[D].吉林大学博士学位论文,2011.
[12]周琳娜,王东明.数字图像取证技术[M].北京：北京邮电大学出版社,2008.
[13]J. Fridrich, R. Du, M. Lomg. Steganalysis LSB Encoding in Color Images[C]. Proceedings IEEE International Conference on Multimedia and Expo,New York City, NY, July 30-Auguest 2,2000:1279-1282.
[14]http://www.jjtc.com/security/stegtools.htm
[15]毛家发,林家骏.基于净图描述的通用隐写分析技术[J].计算机学报,2010,33(2)：569-579.
[16]B. E. Koenig, Authentication of Forensic Audio Recordings [J], Journal of the Audio Engineering Society,1990,38(1):3-33.
[17]B. E. Koenig, D. S. Lacey, S. A. Killion. Forensic Enhancement of Digital Audio Recordings [J], Journal of the Audio Engineering Society,2007,55(5):252-371.
[18]AES Recommended Practice for Forensic Purposes—Managing Recorded Audio Materials Intended for Examination, AES Standard 27-1996
[19]S. Dumitrescu, X. Wu, Z. Wang. Detection of LSB Steganography via Sample Pair Analysis[J]. IEEE Transactions on Signal Processing,2003,51(7):1995-2000.
[20]D. K. Andrew. Steganalysis of Embedding in Two Least-Significant Bits[J]. IEEE Transactions on Information Forensics and Security,2007,2(1):46-54.
[21]B. Li, Y. M. Fang, J. W. Huang. Steganalysis of Mulitple-base Notational System Steganography[J]. IEEE Signal Processing Letters,2008,15:493-496.
[22]刘绍辉,姚鸿勋,高文,姜峰.针对小波域量化隐藏方法的图像检测技术研究[J].通信学报,2004,25(7)：71-77.
[23]B. Li, Y. Q. Shi, J. W. Huang. Steganalysis of YASS[C]. Proceedings of the 10th ACM workshop on Multimedia and security, Oxford, United Kingdom,2008:139-148.
[24]P Moulin, J oseph A. O'Sullivan. InformationTheoretic Analysis of Information Hiding [J]. IEEE Transactions on Information Theory,2003,49 (3):563-593.
[25]钮心忻,杨义先.信息隐写与隐写分析研究框架探讨[J].电子学报,2006,34(12A)：2421-2424.
[26]M H M Costa. Writing on Dirty Paper[J]. IEEE Transactions on Information Theory, 1983,29 (3):439-441.
[27]A. S.Cohen, A. Lapidoth. The Gaussian Watermarking Game[J]. IEEE Transactions on Information Theory,2002,48 (6):1639-1667.
[28]A Somekh Baruch, N Merhav. On The Capacity Game of Public Watermarking Systems[A]. Proceeding of 2002 IEEE International Symposium on Information Theory [C]. Lausanne, Switzerland:IEEE,2002:223-223.
[29]P Moulin, M K Mihcak. The Parallel-Gaussian Watermarking Game[J]. IEEE Transactions on Information Theory,2004,50(2):272-289.
[30]T. Holotyak, J. Fridrich, S. Voloshynovskiy. Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics[A]. In:Processings of 9th IFIP TC-6 TC-11 Conference on Communications and Multimedia Security, Lecture Notes in Computer Science [C],2006,3677:273-274.
[31]X. Y. Luo, D. S. Wang, P. Wang, F. L. Liu. A Review on Blind Detection for Image Steganography [J]. Signal Processing,2008,88(9):2138-2157.
[32]J. Fridrich, M. Goljan. Practical Steganalysis of Digital Image State of TheArt. Security and Watermarking of Multimedia Contents Ⅳ, Proceedings of SPIE [C].2002, 4675:1-13.
[33]C. Rajarathnam, K. Mebdi, N. Memon.Nasir. Image Steganography and Steganalysis: Concepts and Practice[C], International Workshop of Digital Watermarking 2004,2939: 35-49.
[34]梁小萍,何军辉,李健乾,黄继武.隐写分析-原理、现状与展望[J].中山大学学报,2004,43(6)：93-96.
[35]R. Chandramouli, K. P. Subbalakshmi. Current Trends in Steganalysis:A Critical Survey[C], International Conference on Control, Automation, Robotics and Vision, Kunming, China,2004:964-967.
[36]X. Y. Luo, F. L. Liu, S. G. Lian, C. F. Yang, S. Gritzalis. On The Typical Statistic Features for Image Blind Steganalysis [J]. IEEE Journal on Selected Areas in Communications,2011,29(7):1404-1422.
[37]I. Avcibas, N. Memon, B. Sankur, Steganalysis Using Image Quality Metrics[J]. IEEE Transactions on Image Processing,2003,12(2):221-229.
[38]J. J. Harmsen, W. A. Pearlman.Steganalysis of Additive Noise Modelable Information Hiding[C]. In:Proceedings of the SPIE, Security, Steganography, and Watermarking of Multimedia Contents V,2003,5020:131-142.
[39]A. D. Ker, Steganalysis of LSB Matching in Grayscale Images[J]. IEEE Signal Processing Letters,2005,12(6):441-445.
[40]K. Sullivan, U. Madhow, S. Chandrasekaran, B. S. Manjunath.Steganalysis for Markov Cover Data with Applications to Images[J]. IEEE Transactions on Information Forensics and Security,2006,1(2):275-287.
[41]X. C. Chen, Y. H. Wang, T. N. Tan, L. Guo. Blind Image Steganalysis Based on Statistical Analysis of Empirical Matrix[C]. In:Proceedings of 18th International conference on pattern recognition,2006,3:1107-1110.
[42]G. R. Xuan, Y. Q. Shi, C. Huang, et al. Steganalysis Using High-Dimensional Features Derived from Co-occurrence Matrix and Class-wise Non-principal Components Analysis (CNPCA)[C]. In:Proceedings of international workshop on Digital Watermarking, Lecture Notes in Computer Science,2006,4283:49-60.
[43]B. Chen,G. Wornell. Quantization Index Modulation:A Class of Provably Good Methods for Digital Watermarking and Information Embedding[J]. IEEE Transaction on Information Theory,2001,47(4):1423-1443.
[44]http://www.outguess.org/
[45]http://www1.inf.tu-dresden.de/-aw4
[46]P. Sallee. Model Based Steganography[C]. In Kalker, I.J. Cox, and Yong Man Ro, editors, International Workshop on Digital Watermarking, Lecture Notes in Computer Science,2004,2939:154-167.
[47]P. Sallee. Model-Based Methods for Steganography and Steganalysis[J]. International Journal of image Graphics,2005,5(1):167-190,
[48]J. W. Huang, Y. Q. Shi. Adaptive Image Watermarking Scheme Based on Visual Masking[J].Electronics. Letter,1998,34(8):748-750.
[49]W. N. Lie, G. S. Lin, A Feature-Based Classification Technique for Blind Image Steganalysis [J]. IEEE Transactions on Multimedia,2005,7(6):1007-1020.
[50]Y Q. Shi, G. R. Xuan, D. K. Zou, et al. Image Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-error Image, and Neural Network[C]. In:Proceedings of IEEE International Conference on Multimedia and Expo,2005:269-272.
[51]T. Pevny, P. Bas, J. Fridrich. Steganalysis by Subtractive Pixel Adjacency Matrix[C]. Proceedings of the 1 lth ACM workshop on Multimedia and security,2009:75-84.
[52]T. Pevny, P. Bas, J. Fridrich. Steganalysis by Subtractive Pixel Adjacency Matrix[J]. IEEE Transactions on Information Forensics and Security,2010,5(2):215-224.
[53]G. Cancelli, G. Doerr, I. Cox, M. Barni. Detection of Steganography Based on the Amplitude of Histogram Local Extrema[C]. In:IEEE International Conference on Image Processing (ICIP), San Diego, CA,2008:12-15.
[54]M. Goljan, J. Fridrich, T. Holotyak.New Blind Steganalysis and Its Implications[C].In: Processdings of SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, CA, Jan.16-19,2006,6072:1-13.
[55]JP Hide&Seek [Online]. Available:http://linux01.gwdg.de/～ alatham/stego.html
[56]Y. Kim, Z. Duric, D. Richards,et al. Modified Matrix Encoding Technique for Minimal Distortion Steganography[C].In:Processdings of 8th International Workshop on Information Hiding, Alexandria,VA, Jul.10-12,, Lecture Notes in Computer Science, 2006,4437:314-327.
[57]S. Hetzl, P. Mutzel, J. Dittmann. A Graph—Theoretic Approach to Steganography[C]. In:Processding of 9th IFIP TC-6 TC-11 International Conference on Communications and Multimedia Security (CMS 2005), Salzburg, Austria, Sep.19-21, Lecture Notes in Computer Science,2005,3677:119-128.
[58]J. Fridrich, M. Goljan, D. Soukal. Perturbed Quantization Steganography Using Wet Paper Codes[C].In Processding of 6th ACM Multimedia & Security Workshop, Magdeburg, Germany, Sep.20-21,2004:4-15.
[59]K. Solanki, A. Sarkar, B. S. Manjunath. YASS:Yet Another Steganographic Scheme That Resists Blind Steganalysis[C].In Processding of 9th International Workshop on Information Hiding, Saint Malo, France, Jun.11-13, Lecture Notes in Computer Science,2007,4567:16-31.
[60]T. Pevny, J. Fridrich. Merging Markov and DCT Features for Multi-class JPEG Steganalysis[C].In Processding of SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, Feb.1,2007,6505:3 1-3 14.
[61]Q. X. Guan, J. Dong, T. N. Tan. An Effective Image Steganalysis Method Based on Neighborhood Information of Pixels[C]. In:18th IEEE International Conference on Image Processing,2011,2721-2724.
[62]J. Fridrich, J. kodovsky, V. Holub, M. Goljan, Steganalysis of Content-Adaptive Steganography in Spatial Domain[C]. In:Proceedings of the 13th international conference on Information hiding,2011:102-117.
[63]J. Fridrich, J. kodovsky, V. Holub, M. Goljan, Breaking HUGO-the Process Discovery[C]. In:Proceedings of the 13th international conference on Information hiding,2011:85-101.
[64]T. Pevny, T. Filler, P. Bas. Using High-Dimensional Image Models to Perform Highly Undetectable Steganography[C]. In:P. W. L. Fong, R. Bohme, and Rei Safavi-Naini, editors, Information Hiding,12th International Workshop, Lecture Notes in Computer Science, Calgary, Canada, June 28-30,2010:161-177.
[65]T. Pevny.Co-occurrence Steganalysis in High Dimensions[C]. In:Proceedings of the SPIE, Media Watermarking, Security, and Forensics,2012,8303:83030B-83030B-13.
[66]J. Fridrich, J. Kodovsky. Rich Models for Steganalysis of Digital Images[J]. IEEE Transactions on Information Forensics and Security,2012,7(3):868-882.
[67]J. Kodovsky, J. Fridrich, V. Holub. Ensemble Classifiers for Steganalysis of Digital Media[J]. IEEE Transactions on Information Forensics and Security,2012,7(2): 432-444.
[68]W. Luo, F. Huang, J. W. Huang. Edge Adaptive Image Steganography Based on LSB Matching Revisited[J]. IEEE Transactions on Information Forensics and Security, v2010,5(2):201-214.
[69]J. Kodovsky, T. Pevny, J. Fridrich. Modern Steganalysis Can Detect YASS[C].In Processding of SPIE, Electronic Imaging, Security Forensics of Multimedia XII, San Jose, CA, Jan.17-21,2010,7541:0201-02 11.
[70]谭海曙,赵慧民,朱立,郭一缜,丁晓艳.一种基于2D-Markov链模型的图像信息隐藏检测方法[J].中山大学学报,2011,50(3)：53-56.
[71]J. Fridrich.Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes[C]. In:6th Information Hiding Workshop, Lecture Notes in Computer Science,2005,3200:67-81.
[72]S. Lyu, H. Farid.Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines[C].In:F.A.P. Petitcolas (ed.):Information Hiding.5th International Workshop. Lecture Notes in Computer Science,2002,2578:340-354.
[73]S. Lyu, H. Farid, Steganalysis Using Higher-Order Image Statistics [J]. IEEE Transactions on Information Forensics and Security,2006,1(1):111-119.
[74]http://zooid.org/-paul/crypto/jsteg/
[75]www.securityfocus.com/tools/586
[76]T. Holotyak, J. Fridrich, S. Voloshynovskiy.Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics[C]. In:Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security,2005,3677:273-274.
[77]T. Holotyak, J. Fridrich, D. Soukal. Stochastic Approach to Secret Message LengthEstimation in ±k Embedding Steganography[C].In:Processdings of SPIEElectronic Imaging, Security, Steganography, and Watermarking of Multimedia ContentsVII,2005,5681:673-684.
[78]M. Goljan, J. Fridrich, T. Holotyak.New Blind Steganalysis and its Implications, Security[C]. In:Processdings of the SPIE, Steganography, and Watermarking of Multimedia Contents VIII.2006,6072:1-13.
[79]张秋余,张燕,袁占亭.一种新的小波域高阶统计量图像隐写分析方法[J].兰州理工大学学报,2009,35(5)：85-88.
[80]Y. Q. Shi, G. R. Xuan, D. K. Zou, J. J.Gao.Image Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-error Image, and Neural Network[C]. IEEE International Conference on Multimedia and Expo,2005, 269-272.
[81]G. R. Xuan, Y. Q. Shi, J. J. Gao, et al.Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Functions[C]. In:Proceedings of the 7th international conference on Information Hiding,2005:262-277.
[82]Y. Wang,P. Moulin. Optimized Feature Extraction forLearning-Based Image Steganalysis [J]. IEEE Transactions onInformation Forensics and Security,2007,2(1): 31-45.
[83]罗向阳,刘粉林,王道顺.基于小波包分解的图像信息隐写盲检测[J].通信学报,2008,29(10)：173-182.
[84]罗向阳,刘粉林,杨春芳,王道顺.基于最优小波包分解的图像隐写通用检测,2010,40(2)：327-339.
[85]T. Pevny, J. Fridrich.Determining the Stego Algorithm for JPEG Images[C].Special Issue of IEE Proceedings on Information Security,2006,153(3):75-139.
[86]T. Pevny, J. Fridrich.Multiclass Blind Steganalysis for JPEG Images[C].In: Proceedings of SPIE Electronic Imaging,2006:1-13.
[87]T. Pevny, J. Fridrich.Merging Markov and DCT Features for Multi-Class JPEG Steganalysis[C]. In:Proceedings of SPIE Electronic Imaging,2007:03-04.
[88]T. Pevny, J. Fridrich. Multiclass Detector of Current Steganographic Methods for JPEG Format[J]. IEEE Transactions on Information Forensics and Security,2008,3(4): 635-650.
[89]F. J. Huang, B. Li, J. W. Huang.Universal JPEG Steganalysis Based on Microscopic and Macroscopic Calibration[C].15th IEEE International Conference on Image Processing,2008:2068-2071.
[90]F. J. Huang, J. W. Huang. Calibration Based Universal JPEG Steganalysis, Science in China Series F:Information Sciences,2009,52(2):260-268.
[91]黄方军,黄继武.基于图像校准的通用性JPEG隐写分析[J].中国科学F辑：信息科学,2009,39(4)：383-390.
[92]Q. Z. Liu, A. H. Sung. B. M. Ribeiro, R. Ferreira.Steganalysis of Multi-class JPEG Images Based on Expanded Markov Features and Polynomial Fitting[C].IEEE World Congress on Computational Intelligence,2008:3352-3357.
[93]Q. Z. Liu, A. H. Sung, M. Y. Qiao.Improved Detection and Evaluation for JPEG Steganalysis[C]. In:Proceedings of the 17th ACM international conference on Multimedia,2009:873-876.
[94]Q. Z. Liu, A. H. Sung, M. Y. Qiao. Neighboring Joint Density-Based JPEG Steganalysis[J]. ACM Transactions on Intelligent Systems and Technology,2011,2(2): 16:1-16:16.
[95]Q. Z. Liu, A. H. Sunga, M. Y. Qiao, et al. An Improved Approach to Steganalysis of JPEG Images[J]. Information Sciences,2010,180(9):1643-1655.
[96]A. Nissar, A. H. Mir. Classification of Steganalysis techniques:A Study [J].Digital Signal Processing,2010,20:1758-1770.
[97]http://www.cryptobola.com
[98]H. Zong, F. L. Liu, X. Y. Luo. Blind Image Steganalysis Based on Wavelet Coefficient Correlation[J]. Digital Investigation,2012,9(1):58-68.
[99]H. Sajedi, M. Jamzad. A Steganalysis Method Based on Contourlet Transform Coefficients[C].International Conference on Intelligent Information Hiding and Multimedia Signal Processing,2008:245-248.
[100]张敏情,雷雨.基于小波系数相关性的空域隐写分析方法[J].光电子-激光,2012,23(5)：972-979.
[101]郭燕卿,孔祥维,尤新刚,何德全.基于Tri-training半监督学习的JPEG隐密分析方法[J].通信学报,2008,29(10)：205-214.
[102]郭燕卿,孔祥维,尤新刚,何德全.基于共生特征和集成多超球面OC-SVM的JPEG隐密分析方法[J].电子与信息学报,2009,31(5)：1180-1184.
[103]Y. Wang, J. F.Liu, W. M. Zhang, S. G. Lian. Reliable JPEG Steganalysis Based on Multi-directional Correlations [J]. Signal Processing:Image Communication,2010, 25(8):577-587.
[104]毛家发,钮心忻,杨义先,时书剑.基于JPEG净图定量描述的隐写分析方法[J].电子学报,2011,39(8)：1907-1912.
[105]李开达,张涛,李星.基于模糊积分多分类器融合的JPEG图像隐写算法识别[J].信息工程大学学报,2012,13(2)：200-204.
[106]G. Gul, F. Kurugollu. SVD-based Universal Spatial Domain Steganalysis[J]. IEEE Transactions on Information Forensics and Security,2010,5(2):349-353.
[107]G. Gul, A. E. Dirik, I. Avcibas.Steganalytic Features for JPEGCompression Based Perturbed Quantization[J]. IEEE Signal Processing Letter,2007,14(3):205-208.
[108]J. Zhang, D. Zhang. Detection of LSB Matching Steganography in Decompressed Images[J]. IEEE Signal Processing Letters,2010,17(2):141-144.
[109]X. Li, T. Zhang, Y. Zhang, et al. A Novel Blind Detector for Additive Noise Steganography in JPEG Decompressed Images [J]. Multimedia Tools and Applications, Online:DOI:10.1007/s11042-012-1112-2
[110]J. Fridrich, M. Goljan.Digital Image Steganography Using Stochastic Modulation[C]. In:Processdings of SPIE, ElectronicImaging, Security, Steganography, andWatermarking of Multimedia Contents V, Santa Clara, CA,5020:191-202.
[111]W. N. Lie, G. S. Lin. A Feature-Based Classification Technique for Blind Image Steganalysis[J]. IEEE Transactions on Multimedia,2005,7(6):1007-1020.
[112]毛家发,林家骏,戴蒙.基于图像攻击的隐藏信息盲检测技术[J].计算机学报,2009,32(2)：318-327.
[113]毛家发,林家骏.基于净图描述的通用隐写分析技[J].计算机学报,2010,33(3)：569-579.
[114]C.Grigoras.Digital Audio Recording Analysis:the Electric Network Frequency (ENF) Criterion[J]. International Journal of Speech, Language and the Law,2005,12:63-76.
[115]C.Grigoras. Applications of ENF Criterion in Forensics Audio, Video, Computer and Telecommunication Analysis [J]. Forensic Science International,2007,167:136-145.
[116]M. Huijbregtse, Z. Geradts.Using the ENF Criterion for Determining the Time of Recording of Short Digital Audio Recordings[C]. In:Proceedings of the 3rd International Workshop on Computational Forensics, LNCS 5718,2009:116-124.
[117]D. P. N. Rodriguez, J. A. A. Jr., L. W. P. Biscainho.Audio Authenticity:Detecting ENF Discontinuity With High Precision Phase Analysis [J] IEEE Transactions on Information Forensics and Security,2010,5(3):534-543.
[118]R. Yang, Z. H. Qu, J. W. Huang.Detecting Digital Audio Forgeries by Checking Frame Offsets[C]. In:Proceedings of the 10th ACM workshop on Multimedia and Security,2008:21-26.
[119]R. Yang, Y. Q. Shi, J. W. Huang. Defeating Fake-Quality MP3[C]. In:Proceedings of the 1 lth ACM workshop on Multimedia and Security,2009:117-124.
[120]R. Yang, Y. Q. Shi, J. W. Huang.Detecting Double Compression of Audio Signal[C]. In:Proceedings of the SPIE,Media Forensics and Security II. Edited by Memon, Nasir D.; Dittmann, Jana; Alattar, Adnan M.; Delp, Edward J.,2010,7541: 75410K-75410K-10.
[121]Q. Z. Liu, A. H. Sung, M. Y. Qiao. Detection of Double MP3 Compression[J]. Cognitive Computation,2010,2(4):291-296.
[122]M. Y. Qiao, A. H. Sung, Q. Z. Liu. Revealing Real Quality of Double Compressed MP3 Audio[C]. In:Proceedings of the international conference on Multimedia,2010: 1011-1014.
[123]Y. M. Liu, Z. Y. Yuan, P. N. Markham, et al. Application of Power System Frequency for Digital Audio Authentication[J]. IEEE Transactions on Power Delivery,2012, inpress
[124]J. T. Zhou, D. G. Romero, C. E. Wilson.Automatic Speech Codec Identification with Applications to Tampering Detection of Speech Recordings[C]. In:Proceedings of Interspeech,2011:2533-2536.
[125]X. Y. Pan, X. Zhang, S. Lyu.Detecting Splicing in Digital Audios Using Local Noise Level Estimation[C].37th IEEE International Conference on Acoustics, Speech and Signal Processing,2012:1841-1844.
[126]C. Kraetzer, A. Oermann, J. Dittmann, A. Lang.Digital Audio Forensics:AFirst Practical Evaluation on Microphone and Environment Classification[C]. In: Proceedings of the 9th workshop on Multimedia & Security,2007:63-74.
[127]C. Kraetzer, M. Schott, J. Dittmann.Unweighted Fusion in Microphone Forensics using a Decision Tree and Linear Logistic Regression Models[C]. In:Proceedings of the 11th ACM workshop on Multimedia and Security,2009:49-56.
[128]R. Buchholz, C. Kraetzer, J. Dittmann.Microphone Classification Using Fourier Coefficients[C]. In:Proceedings of Information Hiding, Lecture Notes in Computer Science,2009,5806:235-246.
[129]D. G. Romero, C. Y. Espy-Wilson.Automatic Acquisition Device Identification from Speech Recordings[C].IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP),2010:1806-1809.
[130]C.Kraetzer, K. Qian, M. Schott, J. Dittmann.A Context Model for Microphone Forensics and its Application in Evaluations[C]. In:Proceedings of Media Watermarking, Security and ForensicsXIII, IS&T/SPIE Electronic Imaging Conference, 7880,2011.
[131]C.Kraetzer, K. Qian, M. Schott, J. Dittmann.Extending a Context Model for Microphone Forensics[C]. In:Proceedings of the SPIE,Media Watermarking, Security, and Forensics,2012,8303:83030S-83030S-12.
[132]S. Ikram, H. Malik. Microphone Identification using Higher-Order Statistics, AES 46th International Conference,2012:5-2.
[133]H. Q. Vu, S. W. Liu, X. H. Yang, et al. Identifying Microphone from Noisy Recordings by Using Representative Instance One Class-Classification Approach[J]. Journal of Networks,2012,7(6):908-917.
[134]R. G. Malkin, A. Waibel. Classifying User Environment for Mobile Applications Using Linear Autoencoding of Ambient Audio[C].IEEE International Conference on Acoustics, Speech, and Signal Processing,2005,5:509-519.
[135]S. Chu, S. Narayanan, C.C. J. Kuo, M. J. Matari. Where am I? Scene Recognition for Mobile Robots using Audio Features[C].IEEE International Conference on Multimedia and Expo,2006:885-888.
[136]A. J. Eronen, V. T. Peltonen, J. T. Tuomi, et al.Audio-Based Context Recognition[J]. IEEE Transactions on Audio, Speech, and Language Processing,2006,14(1):321-329.
[137]G. Muhammad, K. Alghathbar.Environment Recognition from Audio Using MPEG-7 Features[C]. International Conference on Embedded and Multimedia Computing,2009: 1-6.
[138]H. Malik, H. Farid.Audio Forensics from Acoustic Reverberation[C].IEEE International Conference on Acoustics Speech and Signal Processing,2010: 1710-1713.
[139]C. W.Honsinger, P. Jones, M. Rabbani, et al. Lossless Recovery Of An Original ImageContaining Embedded Data[P]. U.S. Patent 6278791,2001.
[140]Y. J. Hu, H. K. Lee, K. Y. Chen, J. W. Li.Difference Expansion Based Reversible Data Hiding Using Two Embedding Directions [J]. IEEE Transactions on Multimedia,2008, 10(8):1500-1512.
[141]Y. J. Hu, H. K. Lee, J. W. Li.DE-Based Reversible Data Hiding With Improved Overflow Location Map[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(2):250-260.
[142]V. Sachnev, H. J. Kim, J. Nam, et al.Reversible Watermarking Algorithm Using Sorting and Prediction[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(7):989-999.
[143]X. Wang, X. L. Li, B. Yang, Z. M. Guo.Efficient Generalized Integer Transform for Reversible Watermarking [J]. IEEE Signal Processing Letters,2010,17(6):567-570.
[144]X. L. Li, B. Yang, T. Y. Zeng.Efficient Reversible Watermarking Based On Adaptive Prediction-Error Expansion and Pixel Selection[J]. IEEE Transactions on Image Processing,2011,20(12):3524-3533.
[145]D. Coltuc.Improved Embedding for Prediction-Based Reversible Watermarking [J]. IEEE Transactions on Information Forensics and Security,2011,6(3):873-882.
[146]W. M. Zhang, B. Chen, N. H. Yu.Improving Various Reversible Data Hiding Schemes Via Optimal Codes for Binary Covers[J]. IEEE Transactions on Image Processing, 2012,21(6):2991-3003.
[147]Z. C. Ni, Y. Q. Shi, N. Ansari, et al. Robust Lossless Image Data Hiding Designed for Semi-Fragile Image Authentication[J]. IEEE Transactions on Circuits and Systems for Video Technology,2008,18(4):497-509.
[148]L. L. An, X. B. Gao, X. L. Li, et al.Robust Reversible Watermarking via Clustering and Enhanced Pixel-Wise Masking[J]. IEEE Transactions on Image Processing,2012, 21(8):3598-3611.
[149]M. U. Celik, G. Sharma, A. M. Tekalp, E. Saber.Lossless Generalized-LSB Data Embedding[J]. IEEE Transactions on Image Processing,2005,14(2):253-266.
[150]J. Tian.Reversible Data Embedding Using a Difference Expansion[J]. IEEE Transactions on Circuits and Systems for Video Technology,2003,13(8):890-896.
[151]A. M. Alattar.Reversible Watermark Using the Difference Expansion of a Generalized Integer Transform [J]. IEEE Transactions on Image Processing,2004,13(8): 1147-1156.
[152]Z. H. Ni, Y Q. Shi, N. Ansari, W. Su.Reversible Data Hiding[J] IEEE Transactions on Circuits and Systems for Video Technology,2006,16(3):354-362.
[153]W. L. Tai, C. Yeh, C. C. Chang.Reversible Data Hiding Based on Histogram Modification of Pixel Differences[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(6):906-910.
[154]H. T Wu, J. W. Huang.Reversible Image Watermarking on Prediction Errors by Efficient Histogram Modification[J]. Signal Processing,2012,92(12):3000-3009.
[155]D. Coltuc, J. M. Chassery.Very Fast Watermarking by Reversible Contrast Mapping[J]. IEEE Signal Processing Letters,2007,14(4):255-258.
[156]S. W. Weng, Y. Zhao, J. S. Pan, R. R. Ni.Reversible Watermarking Based on Invariability and Adjustmenton Pixel Pairs[J].IEEE Signal Processing,2008, 15:721-724.
[157]H. J. Kim, V. Sachnev, Y. Q. Shi, et al.A Novel Difference Expansion Transform for Reversible Data Embedding[J]. IEEE Transactions on Information Forensics and Security,2008,3(3):456-465.
[158]J. H.He, J. W. Huang. Steganalysis of Stochastic Modulation Steganography[J]. Science in China:Series F Information Sciences,2006,49(3):273-285.
[159]U. Grenander, A. Srivastava.Probability Models for Clutter in natural Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(4):424-429.
[160]G. Schaefer, M. Stich.UCID-An Uncompressed Colour Image Database[C].In: Processding of SPIE, Storage and Retrieval Methods and Applications for Multimedia 2004:472-480.
[161]G. Cancelli, M. Barni, G. Doerr, I. J. Cox.A Comparative Study of ±1 Steganalyzers[C]. In:Proceedings of the IEEE International Workshop on Multimedia Signal Processing,2008:791-796.
[162]J. Fridrich, M. Goljan.A New Steganography Method for Palette Images[C]. In IS&T PICS, Savannah, Georgia,1999:285-289.
[163]J. Fridrich, R. Du. Secure Steganographic Methods for Palette Images[C]. In the 3rd Information Hiding Workshop, Lecture Notes in Computer Science,2000,1768:47-60.
[164]C. H. Tzeng, Z. F. Yang, W. H. Tsai. Adaptive Data Hiding in Palette Images by Color Ordering and Mapping with Security Protection[J]. IEEE Transactions on Communications,2004,52(5):791-800.
[165]X. P. Zhang, S. Z. Wang, Z. Y. Zhou. Multibit Assignment Steganography in Palette Images[J]. IEEE Signal Processing Letters,2008,15:553-556.
[166]A. Westfeld, A. Pfitzmann.Attacks on Steganographic Systems[C]. Lecture Notes in Computer Science, Springer-Verlag, Berlin,2000,1768:61-75.
[167]EzStego, online available:http://www.stegaoarchive.com.
[168]J. Fridrich, M. Goljan, D. Soukal. Higher-order Statistical Steganalysis of Palette Images[C].In:Processdings of SPIE 5020, Security and Watermarking of Multimedia Contents, Santa Clara, CA,2003,178:178-190.
[169]R. Du, L. E. Guthrie, D. Buchy.Steganalysis with JPEG and GIF Images[C]. In: Processdings of SPIE-IS&T Electronic Imaging, Security, Steganography and Watermarking of Multimedia Contents VI, edited by Edward J. Delp III, Ping W. Wong, 2004,5306:98-104
[170]X. P. Zhang, S. Z. Wang. Analysis of Parity Assignment Steganography in Palette Images [J]. Knowledge-Based Intelligent Information and Engineering Systems, Lecture Notes in Artificial Intelligence, Springer-Verlag,2005,3683:1025-1031.
[171]J. H. Qin, X. M. Sun, X. Y. Xiang.Steganalysis Based on lifting Wavelet Transform for Palette Images[C]. International Conference on Computational Intelligence and Security,2007:672-675.
[172]N. F. Johnson, S. Jajodia.Steganalysis of Images Created Using Current Steganography software[C]. In Processdings of Information Hiding, Lecture Notes in Computer Science, Springer-Verlag, Berlin,1998,1525:273-289.
[173]J. Huang, S. R. Kumar, M. Mitra, et al. Spatial Color Indexing and Applications [J]. International Journal of Computer Vision,1999,35(3):245-268.
[174]C. C. Chang, C. J. Lin, LIBSVM:A Library for Support Vector Machines,2001, Software available at http://www.csie.ntu.edu.tw/-cjlin/libsvm
[175]T. Serre, L. Wolf, T. Poggio. Object Recognition with Features Inspired by Visual Cortex[C]. IEEE Conference on Computer Vision and Pattern Recognition,2005,2: 994-1000.
[176]Y. Z. Huang, K. Q. Huang, D. C. Tao, et al. Enhanced Biologically Inspired Model[C]. IEEE Conference on Computer Vision and Pattern Recognition,2008,1-8.
[177]K. Q. Huang, D. C. Tao, Y. Yuan, et al. Biologically Inspired Features for Scene Classification in Video Surveillance[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part B:Cybernetics,2011,41(1):307-313.
[178]G. Soulodre.About This Dereverberation Business:A Method for extracting Reverberation from Audio Signals[C]. AES 129th Convention,2010.
[179]K. Yao, K. K. Paliwal, S. Nakamura.Noise adaptive Speech Recognition Based on Sequential Noise Parameter Estimation[J]. Speech Communication,2004,42(1):5-23.
[180]S.F. Boll.Suppression of Acoustic Noise in Speech Using Spectral Subtraction[J].IEEE Transactions on Acoustics, Speechand Signal Processing,1997, 27(2):113-120.
[181]K. Yao, S. Nakamura.Sequential Noise Compensation by Sequential Monte Carlo Methods[J].Advances in Neural Information Processing Systems,2004,14:1213-1220
[182]R. Singh, B. Raj.Tracking Noise via dynamical Systems with a Continuum of States[C]. In:Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing,2003,1:396-399.
[183]M. Fujimoto, S. Naakamura.Particle filter Based Non-Stationary Noise Tracking For Robust Speech Feature Enhancement[C]. In:Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing,2005:257-260.
[184]F. Faubel, M. Wolfel.Coupling Particle Filters with Automatic Speech Recognition for Speech Feature Enhancement[C]. In:Proceedings of Interspeech,2006:37-40.
[185]M. Wolfel, J. W. McDonough.Distant Speech Recognition[M]. New York:Wiley, 2009.
[186]M. Fujimoto, S. Naakamura.Particle filtering and Polyak Averaging-Based Non-Stationary Noise Tracking for ASR in Noise[C].IEEE Workshop on Automatic Speech Recognition and Understanding,2005:337-342.
[187]M. Wolfel.Enhanced speech Features by Single-Channel Joint Compensation of Noise and Reverberation[J].IEEE Transactions on Audio, Speech, and Language Processing, 2009,17(2):312-323.
[188]B. Ristic, S. Arulampalam, N. Gordon.Beyond the Kalman Filter:Particle Filters for Tracking Application[M].Boston, MA:Artech House,2004.
[189]M. S. Arulampalam, S. Maskell, N. Gordon, T. Clapp.A Tutorial on Particle filters for Online Nonlinear/Non-Gaussian Bayesian Tracking[J]. IEEE Transactions on Signal Processing,2002,50(2):174-188.
[190]W. K. Hastings.Monte Carlo Sampling Methods Using Markov Chains and Their Applications[J].Biometrika,1970,57(1):97-109.
[191]A. Sehr, R. Maas, W. Kellermann.Reverberation Model-Based Decoding in The Logmelspec Domain For Robust Distant-Talking Speech Recognition[J].IEEE Transactions on Audio, Speech and Language Processing,2010,18(7):1676-1691.
[192]FFMPEG, http://www.ffmpeg.org
[2]http://www.washingtonpost.com.
[3]R. C. Maher. Audio Forensic Examination:Authenticity, Enhancement, and Interpretation[J]. IEEE Signal Processing Magazine,2009,26(2):84-94.
[4]吴金海,林福宗.基于数字水印的图像认证技术[J].计算机学报,2004,27(9)：1153-1161.
[5]胡永健,刘琲贝,贺前华.数字多媒体取证技术综述[J].计算机应用,2010,30(3),657-661.
[6]Behrouz A. Forouzan,密码学与网络安全[M].马振晗,贾军保译,北京：清华大学出版社,2009.
[7]I. J. Cox, M. L.Miller, J. A. Bloom,数字水印[M].王颖,黄志蓓等译.北京：电子工业出版社,2003.
[8]http://www.cs.dartmouth.edu/farid/Hany_Farid/Home.html.
[9]T. T. Ng, S. F. Chang, C. Y. Lin. Passive Blind Image Forensics Multimedia Security Technologies for Digital Rights Management[M],2006:383-412.
[10]H. Farid. Creating and Detecting Doctored and Virtual Images:Implications to the Child Pornography Prevention Act [EB/OL]. Technical Report, Department of Computer Science, Dartmouth College, New Hampshire, USA,2004. http://www.ists.dartmouth.edu/library/100.pdf.
[11]陈海鹏.数字图像真伪鉴别技术研究[D].吉林大学博士学位论文,2011.
[12]周琳娜,王东明.数字图像取证技术[M].北京：北京邮电大学出版社,2008.
[13]J. Fridrich, R. Du, M. Lomg. Steganalysis LSB Encoding in Color Images[C]. Proceedings IEEE International Conference on Multimedia and Expo,New York City, NY, July 30-Auguest 2,2000:1279-1282.
[14]http://www.jjtc.com/security/stegtools.htm
[15]毛家发,林家骏.基于净图描述的通用隐写分析技术[J].计算机学报,2010,33(2)：569-579.
[16]B. E. Koenig, Authentication of Forensic Audio Recordings [J], Journal of the Audio Engineering Society,1990,38(1):3-33.
[17]B. E. Koenig, D. S. Lacey, S. A. Killion. Forensic Enhancement of Digital Audio Recordings [J], Journal of the Audio Engineering Society,2007,55(5):252-371.
[18]AES Recommended Practice for Forensic Purposes—Managing Recorded Audio Materials Intended for Examination, AES Standard 27-1996
[19]S. Dumitrescu, X. Wu, Z. Wang. Detection of LSB Steganography via Sample Pair Analysis[J]. IEEE Transactions on Signal Processing,2003,51(7):1995-2000.
[20]D. K. Andrew. Steganalysis of Embedding in Two Least-Significant Bits[J]. IEEE Transactions on Information Forensics and Security,2007,2(1):46-54.
[21]B. Li, Y. M. Fang, J. W. Huang. Steganalysis of Mulitple-base Notational System Steganography[J]. IEEE Signal Processing Letters,2008,15:493-496.
[22]刘绍辉,姚鸿勋,高文,姜峰.针对小波域量化隐藏方法的图像检测技术研究[J].通信学报,2004,25(7)：71-77.
[23]B. Li, Y. Q. Shi, J. W. Huang. Steganalysis of YASS[C]. Proceedings of the 10th ACM workshop on Multimedia and security, Oxford, United Kingdom,2008:139-148.
[24]P Moulin, J oseph A. O'Sullivan. InformationTheoretic Analysis of Information Hiding [J]. IEEE Transactions on Information Theory,2003,49 (3):563-593.
[25]钮心忻,杨义先.信息隐写与隐写分析研究框架探讨[J].电子学报,2006,34(12A)：2421-2424.
[26]M H M Costa. Writing on Dirty Paper[J]. IEEE Transactions on Information Theory, 1983,29 (3):439-441.
[27]A. S.Cohen, A. Lapidoth. The Gaussian Watermarking Game[J]. IEEE Transactions on Information Theory,2002,48 (6):1639-1667.
[28]A Somekh Baruch, N Merhav. On The Capacity Game of Public Watermarking Systems[A]. Proceeding of 2002 IEEE International Symposium on Information Theory [C]. Lausanne, Switzerland:IEEE,2002:223-223.
[29]P Moulin, M K Mihcak. The Parallel-Gaussian Watermarking Game[J]. IEEE Transactions on Information Theory,2004,50(2):272-289.
[30]T. Holotyak, J. Fridrich, S. Voloshynovskiy. Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics[A]. In:Processings of 9th IFIP TC-6 TC-11 Conference on Communications and Multimedia Security, Lecture Notes in Computer Science [C],2006,3677:273-274.
[31]X. Y. Luo, D. S. Wang, P. Wang, F. L. Liu. A Review on Blind Detection for Image Steganography [J]. Signal Processing,2008,88(9):2138-2157.
[32]J. Fridrich, M. Goljan. Practical Steganalysis of Digital Image State of TheArt. Security and Watermarking of Multimedia Contents Ⅳ, Proceedings of SPIE [C].2002, 4675:1-13.
[33]C. Rajarathnam, K. Mebdi, N. Memon.Nasir. Image Steganography and Steganalysis: Concepts and Practice[C], International Workshop of Digital Watermarking 2004,2939: 35-49.
[34]梁小萍,何军辉,李健乾,黄继武.隐写分析-原理、现状与展望[J].中山大学学报,2004,43(6)：93-96.
[35]R. Chandramouli, K. P. Subbalakshmi. Current Trends in Steganalysis:A Critical Survey[C], International Conference on Control, Automation, Robotics and Vision, Kunming, China,2004:964-967.
[36]X. Y. Luo, F. L. Liu, S. G. Lian, C. F. Yang, S. Gritzalis. On The Typical Statistic Features for Image Blind Steganalysis [J]. IEEE Journal on Selected Areas in Communications,2011,29(7):1404-1422.
[37]I. Avcibas, N. Memon, B. Sankur, Steganalysis Using Image Quality Metrics[J]. IEEE Transactions on Image Processing,2003,12(2):221-229.
[38]J. J. Harmsen, W. A. Pearlman.Steganalysis of Additive Noise Modelable Information Hiding[C]. In:Proceedings of the SPIE, Security, Steganography, and Watermarking of Multimedia Contents V,2003,5020:131-142.
[39]A. D. Ker, Steganalysis of LSB Matching in Grayscale Images[J]. IEEE Signal Processing Letters,2005,12(6):441-445.
[40]K. Sullivan, U. Madhow, S. Chandrasekaran, B. S. Manjunath.Steganalysis for Markov Cover Data with Applications to Images[J]. IEEE Transactions on Information Forensics and Security,2006,1(2):275-287.
[41]X. C. Chen, Y. H. Wang, T. N. Tan, L. Guo. Blind Image Steganalysis Based on Statistical Analysis of Empirical Matrix[C]. In:Proceedings of 18th International conference on pattern recognition,2006,3:1107-1110.
[42]G. R. Xuan, Y. Q. Shi, C. Huang, et al. Steganalysis Using High-Dimensional Features Derived from Co-occurrence Matrix and Class-wise Non-principal Components Analysis (CNPCA)[C]. In:Proceedings of international workshop on Digital Watermarking, Lecture Notes in Computer Science,2006,4283:49-60.
[43]B. Chen,G. Wornell. Quantization Index Modulation:A Class of Provably Good Methods for Digital Watermarking and Information Embedding[J]. IEEE Transaction on Information Theory,2001,47(4):1423-1443.
[44]http://www.outguess.org/
[45]http://www1.inf.tu-dresden.de/-aw4
[46]P. Sallee. Model Based Steganography[C]. In Kalker, I.J. Cox, and Yong Man Ro, editors, International Workshop on Digital Watermarking, Lecture Notes in Computer Science,2004,2939:154-167.
[47]P. Sallee. Model-Based Methods for Steganography and Steganalysis[J]. International Journal of image Graphics,2005,5(1):167-190,
[48]J. W. Huang, Y. Q. Shi. Adaptive Image Watermarking Scheme Based on Visual Masking[J].Electronics. Letter,1998,34(8):748-750.
[49]W. N. Lie, G. S. Lin, A Feature-Based Classification Technique for Blind Image Steganalysis [J]. IEEE Transactions on Multimedia,2005,7(6):1007-1020.
[50]Y Q. Shi, G. R. Xuan, D. K. Zou, et al. Image Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-error Image, and Neural Network[C]. In:Proceedings of IEEE International Conference on Multimedia and Expo,2005:269-272.
[51]T. Pevny, P. Bas, J. Fridrich. Steganalysis by Subtractive Pixel Adjacency Matrix[C]. Proceedings of the 1 lth ACM workshop on Multimedia and security,2009:75-84.
[52]T. Pevny, P. Bas, J. Fridrich. Steganalysis by Subtractive Pixel Adjacency Matrix[J]. IEEE Transactions on Information Forensics and Security,2010,5(2):215-224.
[53]G. Cancelli, G. Doerr, I. Cox, M. Barni. Detection of Steganography Based on the Amplitude of Histogram Local Extrema[C]. In:IEEE International Conference on Image Processing (ICIP), San Diego, CA,2008:12-15.
[54]M. Goljan, J. Fridrich, T. Holotyak.New Blind Steganalysis and Its Implications[C].In: Processdings of SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, CA, Jan.16-19,2006,6072:1-13.
[55]JP Hide&Seek [Online]. Available:http://linux01.gwdg.de/～ alatham/stego.html
[56]Y. Kim, Z. Duric, D. Richards,et al. Modified Matrix Encoding Technique for Minimal Distortion Steganography[C].In:Processdings of 8th International Workshop on Information Hiding, Alexandria,VA, Jul.10-12,, Lecture Notes in Computer Science, 2006,4437:314-327.
[57]S. Hetzl, P. Mutzel, J. Dittmann. A Graph—Theoretic Approach to Steganography[C]. In:Processding of 9th IFIP TC-6 TC-11 International Conference on Communications and Multimedia Security (CMS 2005), Salzburg, Austria, Sep.19-21, Lecture Notes in Computer Science,2005,3677:119-128.
[58]J. Fridrich, M. Goljan, D. Soukal. Perturbed Quantization Steganography Using Wet Paper Codes[C].In Processding of 6th ACM Multimedia & Security Workshop, Magdeburg, Germany, Sep.20-21,2004:4-15.
[59]K. Solanki, A. Sarkar, B. S. Manjunath. YASS:Yet Another Steganographic Scheme That Resists Blind Steganalysis[C].In Processding of 9th International Workshop on Information Hiding, Saint Malo, France, Jun.11-13, Lecture Notes in Computer Science,2007,4567:16-31.
[60]T. Pevny, J. Fridrich. Merging Markov and DCT Features for Multi-class JPEG Steganalysis[C].In Processding of SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, Feb.1,2007,6505:3 1-3 14.
[61]Q. X. Guan, J. Dong, T. N. Tan. An Effective Image Steganalysis Method Based on Neighborhood Information of Pixels[C]. In:18th IEEE International Conference on Image Processing,2011,2721-2724.
[62]J. Fridrich, J. kodovsky, V. Holub, M. Goljan, Steganalysis of Content-Adaptive Steganography in Spatial Domain[C]. In:Proceedings of the 13th international conference on Information hiding,2011:102-117.
[63]J. Fridrich, J. kodovsky, V. Holub, M. Goljan, Breaking HUGO-the Process Discovery[C]. In:Proceedings of the 13th international conference on Information hiding,2011:85-101.
[64]T. Pevny, T. Filler, P. Bas. Using High-Dimensional Image Models to Perform Highly Undetectable Steganography[C]. In:P. W. L. Fong, R. Bohme, and Rei Safavi-Naini, editors, Information Hiding,12th International Workshop, Lecture Notes in Computer Science, Calgary, Canada, June 28-30,2010:161-177.
[65]T. Pevny.Co-occurrence Steganalysis in High Dimensions[C]. In:Proceedings of the SPIE, Media Watermarking, Security, and Forensics,2012,8303:83030B-83030B-13.
[66]J. Fridrich, J. Kodovsky. Rich Models for Steganalysis of Digital Images[J]. IEEE Transactions on Information Forensics and Security,2012,7(3):868-882.
[67]J. Kodovsky, J. Fridrich, V. Holub. Ensemble Classifiers for Steganalysis of Digital Media[J]. IEEE Transactions on Information Forensics and Security,2012,7(2): 432-444.
[68]W. Luo, F. Huang, J. W. Huang. Edge Adaptive Image Steganography Based on LSB Matching Revisited[J]. IEEE Transactions on Information Forensics and Security, v2010,5(2):201-214.
[69]J. Kodovsky, T. Pevny, J. Fridrich. Modern Steganalysis Can Detect YASS[C].In Processding of SPIE, Electronic Imaging, Security Forensics of Multimedia XII, San Jose, CA, Jan.17-21,2010,7541:0201-02 11.
[70]谭海曙,赵慧民,朱立,郭一缜,丁晓艳.一种基于2D-Markov链模型的图像信息隐藏检测方法[J].中山大学学报,2011,50(3)：53-56.
[71]J. Fridrich.Feature-Based Steganalysis for JPEG Images and Its Implications for Future Design of Steganographic Schemes[C]. In:6th Information Hiding Workshop, Lecture Notes in Computer Science,2005,3200:67-81.
[72]S. Lyu, H. Farid.Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines[C].In:F.A.P. Petitcolas (ed.):Information Hiding.5th International Workshop. Lecture Notes in Computer Science,2002,2578:340-354.
[73]S. Lyu, H. Farid, Steganalysis Using Higher-Order Image Statistics [J]. IEEE Transactions on Information Forensics and Security,2006,1(1):111-119.
[74]http://zooid.org/-paul/crypto/jsteg/
[75]www.securityfocus.com/tools/586
[76]T. Holotyak, J. Fridrich, S. Voloshynovskiy.Blind Statistical Steganalysis of Additive Steganography Using Wavelet Higher Order Statistics[C]. In:Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security,2005,3677:273-274.
[77]T. Holotyak, J. Fridrich, D. Soukal. Stochastic Approach to Secret Message LengthEstimation in ±k Embedding Steganography[C].In:Processdings of SPIEElectronic Imaging, Security, Steganography, and Watermarking of Multimedia ContentsVII,2005,5681:673-684.
[78]M. Goljan, J. Fridrich, T. Holotyak.New Blind Steganalysis and its Implications, Security[C]. In:Processdings of the SPIE, Steganography, and Watermarking of Multimedia Contents VIII.2006,6072:1-13.
[79]张秋余,张燕,袁占亭.一种新的小波域高阶统计量图像隐写分析方法[J].兰州理工大学学报,2009,35(5)：85-88.
[80]Y. Q. Shi, G. R. Xuan, D. K. Zou, J. J.Gao.Image Steganalysis Based on Moments of Characteristic Functions Using Wavelet Decomposition, Prediction-error Image, and Neural Network[C]. IEEE International Conference on Multimedia and Expo,2005, 269-272.
[81]G. R. Xuan, Y. Q. Shi, J. J. Gao, et al.Steganalysis Based on Multiple Features Formed by Statistical Moments of Wavelet Characteristic Functions[C]. In:Proceedings of the 7th international conference on Information Hiding,2005:262-277.
[82]Y. Wang,P. Moulin. Optimized Feature Extraction forLearning-Based Image Steganalysis [J]. IEEE Transactions onInformation Forensics and Security,2007,2(1): 31-45.
[83]罗向阳,刘粉林,王道顺.基于小波包分解的图像信息隐写盲检测[J].通信学报,2008,29(10)：173-182.
[84]罗向阳,刘粉林,杨春芳,王道顺.基于最优小波包分解的图像隐写通用检测,2010,40(2)：327-339.
[85]T. Pevny, J. Fridrich.Determining the Stego Algorithm for JPEG Images[C].Special Issue of IEE Proceedings on Information Security,2006,153(3):75-139.
[86]T. Pevny, J. Fridrich.Multiclass Blind Steganalysis for JPEG Images[C].In: Proceedings of SPIE Electronic Imaging,2006:1-13.
[87]T. Pevny, J. Fridrich.Merging Markov and DCT Features for Multi-Class JPEG Steganalysis[C]. In:Proceedings of SPIE Electronic Imaging,2007:03-04.
[88]T. Pevny, J. Fridrich. Multiclass Detector of Current Steganographic Methods for JPEG Format[J]. IEEE Transactions on Information Forensics and Security,2008,3(4): 635-650.
[89]F. J. Huang, B. Li, J. W. Huang.Universal JPEG Steganalysis Based on Microscopic and Macroscopic Calibration[C].15th IEEE International Conference on Image Processing,2008:2068-2071.
[90]F. J. Huang, J. W. Huang. Calibration Based Universal JPEG Steganalysis, Science in China Series F:Information Sciences,2009,52(2):260-268.
[91]黄方军,黄继武.基于图像校准的通用性JPEG隐写分析[J].中国科学F辑：信息科学,2009,39(4)：383-390.
[92]Q. Z. Liu, A. H. Sung. B. M. Ribeiro, R. Ferreira.Steganalysis of Multi-class JPEG Images Based on Expanded Markov Features and Polynomial Fitting[C].IEEE World Congress on Computational Intelligence,2008:3352-3357.
[93]Q. Z. Liu, A. H. Sung, M. Y. Qiao.Improved Detection and Evaluation for JPEG Steganalysis[C]. In:Proceedings of the 17th ACM international conference on Multimedia,2009:873-876.
[94]Q. Z. Liu, A. H. Sung, M. Y. Qiao. Neighboring Joint Density-Based JPEG Steganalysis[J]. ACM Transactions on Intelligent Systems and Technology,2011,2(2): 16:1-16:16.
[95]Q. Z. Liu, A. H. Sunga, M. Y. Qiao, et al. An Improved Approach to Steganalysis of JPEG Images[J]. Information Sciences,2010,180(9):1643-1655.
[96]A. Nissar, A. H. Mir. Classification of Steganalysis techniques:A Study [J].Digital Signal Processing,2010,20:1758-1770.
[97]http://www.cryptobola.com
[98]H. Zong, F. L. Liu, X. Y. Luo. Blind Image Steganalysis Based on Wavelet Coefficient Correlation[J]. Digital Investigation,2012,9(1):58-68.
[99]H. Sajedi, M. Jamzad. A Steganalysis Method Based on Contourlet Transform Coefficients[C].International Conference on Intelligent Information Hiding and Multimedia Signal Processing,2008:245-248.
[100]张敏情,雷雨.基于小波系数相关性的空域隐写分析方法[J].光电子-激光,2012,23(5)：972-979.
[101]郭燕卿,孔祥维,尤新刚,何德全.基于Tri-training半监督学习的JPEG隐密分析方法[J].通信学报,2008,29(10)：205-214.
[102]郭燕卿,孔祥维,尤新刚,何德全.基于共生特征和集成多超球面OC-SVM的JPEG隐密分析方法[J].电子与信息学报,2009,31(5)：1180-1184.
[103]Y. Wang, J. F.Liu, W. M. Zhang, S. G. Lian. Reliable JPEG Steganalysis Based on Multi-directional Correlations [J]. Signal Processing:Image Communication,2010, 25(8):577-587.
[104]毛家发,钮心忻,杨义先,时书剑.基于JPEG净图定量描述的隐写分析方法[J].电子学报,2011,39(8)：1907-1912.
[105]李开达,张涛,李星.基于模糊积分多分类器融合的JPEG图像隐写算法识别[J].信息工程大学学报,2012,13(2)：200-204.
[106]G. Gul, F. Kurugollu. SVD-based Universal Spatial Domain Steganalysis[J]. IEEE Transactions on Information Forensics and Security,2010,5(2):349-353.
[107]G. Gul, A. E. Dirik, I. Avcibas.Steganalytic Features for JPEGCompression Based Perturbed Quantization[J]. IEEE Signal Processing Letter,2007,14(3):205-208.
[108]J. Zhang, D. Zhang. Detection of LSB Matching Steganography in Decompressed Images[J]. IEEE Signal Processing Letters,2010,17(2):141-144.
[109]X. Li, T. Zhang, Y. Zhang, et al. A Novel Blind Detector for Additive Noise Steganography in JPEG Decompressed Images [J]. Multimedia Tools and Applications, Online:DOI:10.1007/s11042-012-1112-2
[110]J. Fridrich, M. Goljan.Digital Image Steganography Using Stochastic Modulation[C]. In:Processdings of SPIE, ElectronicImaging, Security, Steganography, andWatermarking of Multimedia Contents V, Santa Clara, CA,5020:191-202.
[111]W. N. Lie, G. S. Lin. A Feature-Based Classification Technique for Blind Image Steganalysis[J]. IEEE Transactions on Multimedia,2005,7(6):1007-1020.
[112]毛家发,林家骏,戴蒙.基于图像攻击的隐藏信息盲检测技术[J].计算机学报,2009,32(2)：318-327.
[113]毛家发,林家骏.基于净图描述的通用隐写分析技[J].计算机学报,2010,33(3)：569-579.
[114]C.Grigoras.Digital Audio Recording Analysis:the Electric Network Frequency (ENF) Criterion[J]. International Journal of Speech, Language and the Law,2005,12:63-76.
[115]C.Grigoras. Applications of ENF Criterion in Forensics Audio, Video, Computer and Telecommunication Analysis [J]. Forensic Science International,2007,167:136-145.
[116]M. Huijbregtse, Z. Geradts.Using the ENF Criterion for Determining the Time of Recording of Short Digital Audio Recordings[C]. In:Proceedings of the 3rd International Workshop on Computational Forensics, LNCS 5718,2009:116-124.
[117]D. P. N. Rodriguez, J. A. A. Jr., L. W. P. Biscainho.Audio Authenticity:Detecting ENF Discontinuity With High Precision Phase Analysis [J] IEEE Transactions on Information Forensics and Security,2010,5(3):534-543.
[118]R. Yang, Z. H. Qu, J. W. Huang.Detecting Digital Audio Forgeries by Checking Frame Offsets[C]. In:Proceedings of the 10th ACM workshop on Multimedia and Security,2008:21-26.
[119]R. Yang, Y. Q. Shi, J. W. Huang. Defeating Fake-Quality MP3[C]. In:Proceedings of the 1 lth ACM workshop on Multimedia and Security,2009:117-124.
[120]R. Yang, Y. Q. Shi, J. W. Huang.Detecting Double Compression of Audio Signal[C]. In:Proceedings of the SPIE,Media Forensics and Security II. Edited by Memon, Nasir D.; Dittmann, Jana; Alattar, Adnan M.; Delp, Edward J.,2010,7541: 75410K-75410K-10.
[121]Q. Z. Liu, A. H. Sung, M. Y. Qiao. Detection of Double MP3 Compression[J]. Cognitive Computation,2010,2(4):291-296.
[122]M. Y. Qiao, A. H. Sung, Q. Z. Liu. Revealing Real Quality of Double Compressed MP3 Audio[C]. In:Proceedings of the international conference on Multimedia,2010: 1011-1014.
[123]Y. M. Liu, Z. Y. Yuan, P. N. Markham, et al. Application of Power System Frequency for Digital Audio Authentication[J]. IEEE Transactions on Power Delivery,2012, inpress
[124]J. T. Zhou, D. G. Romero, C. E. Wilson.Automatic Speech Codec Identification with Applications to Tampering Detection of Speech Recordings[C]. In:Proceedings of Interspeech,2011:2533-2536.
[125]X. Y. Pan, X. Zhang, S. Lyu.Detecting Splicing in Digital Audios Using Local Noise Level Estimation[C].37th IEEE International Conference on Acoustics, Speech and Signal Processing,2012:1841-1844.
[126]C. Kraetzer, A. Oermann, J. Dittmann, A. Lang.Digital Audio Forensics:AFirst Practical Evaluation on Microphone and Environment Classification[C]. In: Proceedings of the 9th workshop on Multimedia & Security,2007:63-74.
[127]C. Kraetzer, M. Schott, J. Dittmann.Unweighted Fusion in Microphone Forensics using a Decision Tree and Linear Logistic Regression Models[C]. In:Proceedings of the 11th ACM workshop on Multimedia and Security,2009:49-56.
[128]R. Buchholz, C. Kraetzer, J. Dittmann.Microphone Classification Using Fourier Coefficients[C]. In:Proceedings of Information Hiding, Lecture Notes in Computer Science,2009,5806:235-246.
[129]D. G. Romero, C. Y. Espy-Wilson.Automatic Acquisition Device Identification from Speech Recordings[C].IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP),2010:1806-1809.
[130]C.Kraetzer, K. Qian, M. Schott, J. Dittmann.A Context Model for Microphone Forensics and its Application in Evaluations[C]. In:Proceedings of Media Watermarking, Security and ForensicsXIII, IS&T/SPIE Electronic Imaging Conference, 7880,2011.
[131]C.Kraetzer, K. Qian, M. Schott, J. Dittmann.Extending a Context Model for Microphone Forensics[C]. In:Proceedings of the SPIE,Media Watermarking, Security, and Forensics,2012,8303:83030S-83030S-12.
[132]S. Ikram, H. Malik. Microphone Identification using Higher-Order Statistics, AES 46th International Conference,2012:5-2.
[133]H. Q. Vu, S. W. Liu, X. H. Yang, et al. Identifying Microphone from Noisy Recordings by Using Representative Instance One Class-Classification Approach[J]. Journal of Networks,2012,7(6):908-917.
[134]R. G. Malkin, A. Waibel. Classifying User Environment for Mobile Applications Using Linear Autoencoding of Ambient Audio[C].IEEE International Conference on Acoustics, Speech, and Signal Processing,2005,5:509-519.
[135]S. Chu, S. Narayanan, C.C. J. Kuo, M. J. Matari. Where am I? Scene Recognition for Mobile Robots using Audio Features[C].IEEE International Conference on Multimedia and Expo,2006:885-888.
[136]A. J. Eronen, V. T. Peltonen, J. T. Tuomi, et al.Audio-Based Context Recognition[J]. IEEE Transactions on Audio, Speech, and Language Processing,2006,14(1):321-329.
[137]G. Muhammad, K. Alghathbar.Environment Recognition from Audio Using MPEG-7 Features[C]. International Conference on Embedded and Multimedia Computing,2009: 1-6.
[138]H. Malik, H. Farid.Audio Forensics from Acoustic Reverberation[C].IEEE International Conference on Acoustics Speech and Signal Processing,2010: 1710-1713.
[139]C. W.Honsinger, P. Jones, M. Rabbani, et al. Lossless Recovery Of An Original ImageContaining Embedded Data[P]. U.S. Patent 6278791,2001.
[140]Y. J. Hu, H. K. Lee, K. Y. Chen, J. W. Li.Difference Expansion Based Reversible Data Hiding Using Two Embedding Directions [J]. IEEE Transactions on Multimedia,2008, 10(8):1500-1512.
[141]Y. J. Hu, H. K. Lee, J. W. Li.DE-Based Reversible Data Hiding With Improved Overflow Location Map[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(2):250-260.
[142]V. Sachnev, H. J. Kim, J. Nam, et al.Reversible Watermarking Algorithm Using Sorting and Prediction[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(7):989-999.
[143]X. Wang, X. L. Li, B. Yang, Z. M. Guo.Efficient Generalized Integer Transform for Reversible Watermarking [J]. IEEE Signal Processing Letters,2010,17(6):567-570.
[144]X. L. Li, B. Yang, T. Y. Zeng.Efficient Reversible Watermarking Based On Adaptive Prediction-Error Expansion and Pixel Selection[J]. IEEE Transactions on Image Processing,2011,20(12):3524-3533.
[145]D. Coltuc.Improved Embedding for Prediction-Based Reversible Watermarking [J]. IEEE Transactions on Information Forensics and Security,2011,6(3):873-882.
[146]W. M. Zhang, B. Chen, N. H. Yu.Improving Various Reversible Data Hiding Schemes Via Optimal Codes for Binary Covers[J]. IEEE Transactions on Image Processing, 2012,21(6):2991-3003.
[147]Z. C. Ni, Y. Q. Shi, N. Ansari, et al. Robust Lossless Image Data Hiding Designed for Semi-Fragile Image Authentication[J]. IEEE Transactions on Circuits and Systems for Video Technology,2008,18(4):497-509.
[148]L. L. An, X. B. Gao, X. L. Li, et al.Robust Reversible Watermarking via Clustering and Enhanced Pixel-Wise Masking[J]. IEEE Transactions on Image Processing,2012, 21(8):3598-3611.
[149]M. U. Celik, G. Sharma, A. M. Tekalp, E. Saber.Lossless Generalized-LSB Data Embedding[J]. IEEE Transactions on Image Processing,2005,14(2):253-266.
[150]J. Tian.Reversible Data Embedding Using a Difference Expansion[J]. IEEE Transactions on Circuits and Systems for Video Technology,2003,13(8):890-896.
[151]A. M. Alattar.Reversible Watermark Using the Difference Expansion of a Generalized Integer Transform [J]. IEEE Transactions on Image Processing,2004,13(8): 1147-1156.
[152]Z. H. Ni, Y Q. Shi, N. Ansari, W. Su.Reversible Data Hiding[J] IEEE Transactions on Circuits and Systems for Video Technology,2006,16(3):354-362.
[153]W. L. Tai, C. Yeh, C. C. Chang.Reversible Data Hiding Based on Histogram Modification of Pixel Differences[J]. IEEE Transactions on Circuits and Systems for Video Technology,2009,19(6):906-910.
[154]H. T Wu, J. W. Huang.Reversible Image Watermarking on Prediction Errors by Efficient Histogram Modification[J]. Signal Processing,2012,92(12):3000-3009.
[155]D. Coltuc, J. M. Chassery.Very Fast Watermarking by Reversible Contrast Mapping[J]. IEEE Signal Processing Letters,2007,14(4):255-258.
[156]S. W. Weng, Y. Zhao, J. S. Pan, R. R. Ni.Reversible Watermarking Based on Invariability and Adjustmenton Pixel Pairs[J].IEEE Signal Processing,2008, 15:721-724.
[157]H. J. Kim, V. Sachnev, Y. Q. Shi, et al.A Novel Difference Expansion Transform for Reversible Data Embedding[J]. IEEE Transactions on Information Forensics and Security,2008,3(3):456-465.
[158]J. H.He, J. W. Huang. Steganalysis of Stochastic Modulation Steganography[J]. Science in China:Series F Information Sciences,2006,49(3):273-285.
[159]U. Grenander, A. Srivastava.Probability Models for Clutter in natural Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(4):424-429.
[160]G. Schaefer, M. Stich.UCID-An Uncompressed Colour Image Database[C].In: Processding of SPIE, Storage and Retrieval Methods and Applications for Multimedia 2004:472-480.
[161]G. Cancelli, M. Barni, G. Doerr, I. J. Cox.A Comparative Study of ±1 Steganalyzers[C]. In:Proceedings of the IEEE International Workshop on Multimedia Signal Processing,2008:791-796.
[162]J. Fridrich, M. Goljan.A New Steganography Method for Palette Images[C]. In IS&T PICS, Savannah, Georgia,1999:285-289.
[163]J. Fridrich, R. Du. Secure Steganographic Methods for Palette Images[C]. In the 3rd Information Hiding Workshop, Lecture Notes in Computer Science,2000,1768:47-60.
[164]C. H. Tzeng, Z. F. Yang, W. H. Tsai. Adaptive Data Hiding in Palette Images by Color Ordering and Mapping with Security Protection[J]. IEEE Transactions on Communications,2004,52(5):791-800.
[165]X. P. Zhang, S. Z. Wang, Z. Y. Zhou. Multibit Assignment Steganography in Palette Images[J]. IEEE Signal Processing Letters,2008,15:553-556.
[166]A. Westfeld, A. Pfitzmann.Attacks on Steganographic Systems[C]. Lecture Notes in Computer Science, Springer-Verlag, Berlin,2000,1768:61-75.
[167]EzStego, online available:http://www.stegaoarchive.com.
[168]J. Fridrich, M. Goljan, D. Soukal. Higher-order Statistical Steganalysis of Palette Images[C].In:Processdings of SPIE 5020, Security and Watermarking of Multimedia Contents, Santa Clara, CA,2003,178:178-190.
[169]R. Du, L. E. Guthrie, D. Buchy.Steganalysis with JPEG and GIF Images[C]. In: Processdings of SPIE-IS&T Electronic Imaging, Security, Steganography and Watermarking of Multimedia Contents VI, edited by Edward J. Delp III, Ping W. Wong, 2004,5306:98-104
[170]X. P. Zhang, S. Z. Wang. Analysis of Parity Assignment Steganography in Palette Images [J]. Knowledge-Based Intelligent Information and Engineering Systems, Lecture Notes in Artificial Intelligence, Springer-Verlag,2005,3683:1025-1031.
[171]J. H. Qin, X. M. Sun, X. Y. Xiang.Steganalysis Based on lifting Wavelet Transform for Palette Images[C]. International Conference on Computational Intelligence and Security,2007:672-675.
[172]N. F. Johnson, S. Jajodia.Steganalysis of Images Created Using Current Steganography software[C]. In Processdings of Information Hiding, Lecture Notes in Computer Science, Springer-Verlag, Berlin,1998,1525:273-289.
[173]J. Huang, S. R. Kumar, M. Mitra, et al. Spatial Color Indexing and Applications [J]. International Journal of Computer Vision,1999,35(3):245-268.
[174]C. C. Chang, C. J. Lin, LIBSVM:A Library for Support Vector Machines,2001, Software available at http://www.csie.ntu.edu.tw/-cjlin/libsvm
[175]T. Serre, L. Wolf, T. Poggio. Object Recognition with Features Inspired by Visual Cortex[C]. IEEE Conference on Computer Vision and Pattern Recognition,2005,2: 994-1000.
[176]Y. Z. Huang, K. Q. Huang, D. C. Tao, et al. Enhanced Biologically Inspired Model[C]. IEEE Conference on Computer Vision and Pattern Recognition,2008,1-8.
[177]K. Q. Huang, D. C. Tao, Y. Yuan, et al. Biologically Inspired Features for Scene Classification in Video Surveillance[J]. IEEE Transactions on Systems, Man, and Cybernetics-Part B:Cybernetics,2011,41(1):307-313.
[178]G. Soulodre.About This Dereverberation Business:A Method for extracting Reverberation from Audio Signals[C]. AES 129th Convention,2010.
[179]K. Yao, K. K. Paliwal, S. Nakamura.Noise adaptive Speech Recognition Based on Sequential Noise Parameter Estimation[J]. Speech Communication,2004,42(1):5-23.
[180]S.F. Boll.Suppression of Acoustic Noise in Speech Using Spectral Subtraction[J].IEEE Transactions on Acoustics, Speechand Signal Processing,1997, 27(2):113-120.
[181]K. Yao, S. Nakamura.Sequential Noise Compensation by Sequential Monte Carlo Methods[J].Advances in Neural Information Processing Systems,2004,14:1213-1220
[182]R. Singh, B. Raj.Tracking Noise via dynamical Systems with a Continuum of States[C]. In:Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing,2003,1:396-399.
[183]M. Fujimoto, S. Naakamura.Particle filter Based Non-Stationary Noise Tracking For Robust Speech Feature Enhancement[C]. In:Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing,2005:257-260.
[184]F. Faubel, M. Wolfel.Coupling Particle Filters with Automatic Speech Recognition for Speech Feature Enhancement[C]. In:Proceedings of Interspeech,2006:37-40.
[185]M. Wolfel, J. W. McDonough.Distant Speech Recognition[M]. New York:Wiley, 2009.
[186]M. Fujimoto, S. Naakamura.Particle filtering and Polyak Averaging-Based Non-Stationary Noise Tracking for ASR in Noise[C].IEEE Workshop on Automatic Speech Recognition and Understanding,2005:337-342.
[187]M. Wolfel.Enhanced speech Features by Single-Channel Joint Compensation of Noise and Reverberation[J].IEEE Transactions on Audio, Speech, and Language Processing, 2009,17(2):312-323.
[188]B. Ristic, S. Arulampalam, N. Gordon.Beyond the Kalman Filter:Particle Filters for Tracking Application[M].Boston, MA:Artech House,2004.
[189]M. S. Arulampalam, S. Maskell, N. Gordon, T. Clapp.A Tutorial on Particle filters for Online Nonlinear/Non-Gaussian Bayesian Tracking[J]. IEEE Transactions on Signal Processing,2002,50(2):174-188.
[190]W. K. Hastings.Monte Carlo Sampling Methods Using Markov Chains and Their Applications[J].Biometrika,1970,57(1):97-109.
[191]A. Sehr, R. Maas, W. Kellermann.Reverberation Model-Based Decoding in The Logmelspec Domain For Robust Distant-Talking Speech Recognition[J].IEEE Transactions on Audio, Speech and Language Processing,2010,18(7):1676-1691.
[192]FFMPEG, http://www.ffmpeg.org
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |