视频隐写检测技术研究
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摘要
视频隐写是信息隐藏近来的研究热点,各种隐写算法不断出现,加强视频隐写监控,确保视频隐写技术不被非法使用已经成为国家信息安全的重要组成部分。视频隐写检测是对视频隐写的攻击技术,它能解决视频隐写监控问题。本文对视频隐写检测技术进行了研究,主要研究内容包括:
1.对视频隐写和隐写检测技术进行了深入分析。对视频隐写技术原理和特点进行了介绍,并对现有隐写算法进行分类,指出结合编码特点的隐写算法是未来发展方向。对视频隐写检测技术进行分类,并对现有的隐写检测现状进行总结,指出视频隐写检测急需解决的问题。
2.针对扩频视频隐写检测,提出了基于帧重构的视频隐写检测算法。分析了扩频隐写原理并总结扩频隐写的特点,采用自适应邻域技术重构视频,计算待测视频与重构视频的差值并提取检测特征,最后设计了KNN分类器。实验结果表明,算法能有效地实现对扩频视频隐写检测。
3.提出了针对运动向量隐写的检测算法。对运动向量隐写算法进行了分析,针对运动向量的时间变化,定义运动向量随机序列,将频率测试和游程测试得到的统计量作为运动向量帧内特征;针对运动向量的空间变化,定义运动向量的二值结构模式,将相邻帧的互信息作为运动向量帧间特征。最后基于运动向量的帧内和帧间特征,设计了针对运动向量隐写的检测算法,实验表明该算法能对运动向量隐写实施有效检测。
最后,总结本文的工作,并对视频隐写分析技术的发展进行了展望,指出未来的研究方向和构想。
Video data hiding has become the focus of information hiding recently, and kinds of algorithms have appeared. The supervisal to video steganography for preventing the illegal use of video steganography has been an important content of national security. Video steganalysis is the attack to the video steganography, which can solve problem of supervisal. In this paper, video steganalysis based on videos was discussed. The main contributions can be summarized as follows:
1. Video steganography and steganalysis are investigated. The theory and characteristics of video hiding is introduced. Based on the classification of the existing video hiding algorithms, a conclusion that video coding would become the future orientation of video hiding is obtained. Then, video detection algorithms are classified, the actuality of which is concluded, and the problem in video steganalysis needed to be solved are pointed out.
2. A video detection algorithm based on the frame reconstructure is proposed to detect the spread spectrum video data hiding. The theory and characteristics of spread spectrum steganography are analyzed and the technique of adaptive neighborhood is adopted to reconstruct the video. The difference between video and its reconstruct video is extracted as the feature for detection. Finally, KNN classifier is devised and the experiment is taken, the results of which shows that the algorithm can detect the video spread spectrum steganography effectively.
3. A detection algorithm to attack the steganographic algorithm based on Motion vector (MV) is prevented. The steganographic algorithm based on MV is analyzed. Considering the time change of MV, the random sequence of MV is defined and the statistics got by frequency test and run test are used as the feature in frame of MV. Referring to the spatial change of MV, the mode of binary structure of MV is defined and the mutual information between neighbor frames is extracted as the feature between frames. Finally, based on the features extracted, a detection algorithm is devised and the experiment show the steganography based on MV can be detected effectively.
Finally, the work of this paper is concluded. The further research topics about video hiding detection technique are outlined, and the research directions in future are discussed.
1.对视频隐写和隐写检测技术进行了深入分析。对视频隐写技术原理和特点进行了介绍,并对现有隐写算法进行分类,指出结合编码特点的隐写算法是未来发展方向。对视频隐写检测技术进行分类,并对现有的隐写检测现状进行总结,指出视频隐写检测急需解决的问题。
2.针对扩频视频隐写检测,提出了基于帧重构的视频隐写检测算法。分析了扩频隐写原理并总结扩频隐写的特点,采用自适应邻域技术重构视频,计算待测视频与重构视频的差值并提取检测特征,最后设计了KNN分类器。实验结果表明,算法能有效地实现对扩频视频隐写检测。
3.提出了针对运动向量隐写的检测算法。对运动向量隐写算法进行了分析,针对运动向量的时间变化,定义运动向量随机序列,将频率测试和游程测试得到的统计量作为运动向量帧内特征;针对运动向量的空间变化,定义运动向量的二值结构模式,将相邻帧的互信息作为运动向量帧间特征。最后基于运动向量的帧内和帧间特征,设计了针对运动向量隐写的检测算法,实验表明该算法能对运动向量隐写实施有效检测。
最后,总结本文的工作,并对视频隐写分析技术的发展进行了展望,指出未来的研究方向和构想。
Video data hiding has become the focus of information hiding recently, and kinds of algorithms have appeared. The supervisal to video steganography for preventing the illegal use of video steganography has been an important content of national security. Video steganalysis is the attack to the video steganography, which can solve problem of supervisal. In this paper, video steganalysis based on videos was discussed. The main contributions can be summarized as follows:
1. Video steganography and steganalysis are investigated. The theory and characteristics of video hiding is introduced. Based on the classification of the existing video hiding algorithms, a conclusion that video coding would become the future orientation of video hiding is obtained. Then, video detection algorithms are classified, the actuality of which is concluded, and the problem in video steganalysis needed to be solved are pointed out.
2. A video detection algorithm based on the frame reconstructure is proposed to detect the spread spectrum video data hiding. The theory and characteristics of spread spectrum steganography are analyzed and the technique of adaptive neighborhood is adopted to reconstruct the video. The difference between video and its reconstruct video is extracted as the feature for detection. Finally, KNN classifier is devised and the experiment is taken, the results of which shows that the algorithm can detect the video spread spectrum steganography effectively.
3. A detection algorithm to attack the steganographic algorithm based on Motion vector (MV) is prevented. The steganographic algorithm based on MV is analyzed. Considering the time change of MV, the random sequence of MV is defined and the statistics got by frequency test and run test are used as the feature in frame of MV. Referring to the spatial change of MV, the mode of binary structure of MV is defined and the mutual information between neighbor frames is extracted as the feature between frames. Finally, based on the features extracted, a detection algorithm is devised and the experiment show the steganography based on MV can be detected effectively.
Finally, the work of this paper is concluded. The further research topics about video hiding detection technique are outlined, and the research directions in future are discussed.
引文
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[2]张立和,周继车,陈伟.透视信息隐藏[M].北京:国防工业出版社,2007.
[3]G.J.Simmons.The Prisoners' problem and the Subliminal Channel[J].Proceedings of CRYPTO'83,1984:81-57.
[4]钮心忻.信息隐藏与数字水印[M].北京:北京邮电大学出版社,2004.
[5]苏育挺,王莉莉,张春田。一种新型视频信息隐藏分析算法.[C]第七届全国信息隐藏暨多媒体信息安全学术大会论文集,2007.
[6]Udit Budhia,Deepa Kundur,Takis Zoumtos.Digital Video Steganalysis Exploiting Statistical Visibility in the Temporal[J].IEEE,2006.
[7]JulienS.Jainsky,DeepaKundur,DonR.Halverson,Towards Digital video steganalysis using asymptotic memoryless detection[J].2007 ACM 978-1-59593-857-2/07/0009.
[8]G.J.Simmons.The Prisoners' problem and the.Subliminal Channel[J].Proceedings of CRYPTO'83,1984,:81-57_
[9]徐长勇,平西建,张涛.视频信息伪装技术综述[J].计算机应用研究,2006.
[10]刘雅宁,压缩域视频水印技术研究[D].陕西:西安电子科技大学,2007.
[11]刘丽,彭代渊,李晓举.低抗线性共谋攻击的空域自适应视频水印方案[J].西南交通大学学报,2007年8月,第42卷,第4期.
[12]Mitchell D.Swanson,Bin Zhu,Ahmed H.Tewfik.Data Hiding for Video-in-Video[J].IEEE,1997,0-8186-8183-7/97.
[13]J.J.Chae,B.S.Manjunath.Data Hiding in Video[J].IEEE,1999,0-7803-5467-2/99.
[14]Bian Yang a,Martin Schmucker b,Xiamu Niu b,Christoph Busch b,Shenghe Sun,Integer DCT Based Reversible Image Watermarking by Adaptive Coefficient Modification[J].Proc.of SPIE-IS&T Electronic Imaging,2005,5681:218-229.
[15]杨晓元,钮可,魏萍,王育民,一种抗几何攻击的视频水印算法[J],计算机工程,2007年4月,33-8.
[16]孙建德,抗时间同步攻击的数宁视频水印方法研究[D].山东:山东大学,2005年4月.
[17]Frank hartung,Student Member,IEEE,Martin kutter.Multimedia Watermarking Techniques[J[.IEEE,1999.
[18]罗楠,基于视频的信息隐藏披术[D].陕西:西安电子科技大学,2007年1月.
[19]张立和,米晓莉,孔祥维,基于运动速度的视步负水印算法[J],计算机应用研究,2007年4月,24-4.
[20]戴侃斐,陈真勇,唐龙,基于运动矢量的抗几何攻击视频水印方案[J].中国图象图形学报,2007年9月,12-9.
[21]Jie Song,K.J.R.Liu,A Data Embedding Scheme for H.263 Compatible Video Coding [J].IEEE,1999,0-7803-5471-0/99.
[22]朱仲杰,蒋刚毅,郁梅,刘晓,吴训威.MPEG-2压缩域的视频数字水印新算法[J].电子学报,2004,(32)1:21-24
[23]Bodo.Y,N.Laurent,Dugelay.Watermarking video,hierarchical embedding in motion vectors[C].Proceedings of International Conference on Image Processing,Piscataway,NJ,USA:IEEE,2003.739-742.
[24]Zhang J,Li J G,Zhang L.Video technique watermark in motion vector[C].ⅩⅣ Brazilian Symposium on Computer Graphics and linage Processing,Florianopolis,Brazil:Oct 2001 Page(s):179-182.
[25]Yulin Wang,Alan Pearmain.Robust Data Hiding in Mpeg-2 Video Against Transcoding[C].EC-VIP-MC 2003,4th EURASIP Conference focused on Video/Image Processing and Multimedia Communications,2-5 July 2003,Zagreb,Croatia.
[26]G.C.Langelaar,R.L.Lagaendijk,and J.Biemond.Real-time labeling of MPEG-2 compressed video[J].Visual Commun Image Representation,1998,11,vol.9,no.4,pp.256-270.
[27]江滨,基于静态数字图像的隐藏信息检测技术研究[D].河南:信息工程大学,2007,6..
[28]夏煜,郎荣玲,黄冠中,黄殿中,钱思进.基于图像的信息隐藏分析技术综述[J],计算机工程,2003.29(7):1-3.
[29]王朔中,张新鹏,张开文,数字密写和密写分析-互联网时代的信息战技术[M].北京,清华大学出版社,2005,4.
[30]Ingemar J.Cox,Joe Kiliant,Tom Leighton,and Talal Shamoon,Secure Spread Spectrum Watermarking for Images,Audio and Video[J].IEEE,1996,0-7803-3258-X/96.
[31]Mobasseri B.G.Direct sequence watermarking of digital Video using m-frames[C].Yhe Proceedings of (?)P98.Vol.2,pp.399-403,1998.
[32]Yongdong Wu,Linear Combination Collusion Attack and its Application on an Anti-Collusion Fingerprinting[J].IEEE,2005,0-7803-8874-7/05.
[33]H.Vicky Zhao,Member,IEEE,Min Wu,Z.jane Wang,Member,IEEE,and K.J.Ray Liu,Fellow,IEEE,Forensic Analysis of Nonl inear Col lusion Attacks for Multimedia Fingerprinting[J].IEEE,2005,1057-7149.
[34]R.Gordon and R.M.Rangayyan.Feature Enhancement of film Mammograms using Fixed and Adaptive Neighborhoods.[J].IEEE Appl.Opt.1984,23(4):560-564.
[35]张晓星,基于块匹配的运动估计算法研究与实现[D].北京:北京交通大学,2008.
[36]吴思,视频运动信息分析技术研究[D].中国科学院研究生院,2005.
[37]朱磊,基于自适应领域概念的视频图像处理技术研究[D].中国科学技术大学,2007.
[38]Aishy Amer,Amar Mitiche,Eric Dubois,Reliable and Fast Structure-oriented Video Noise Estimation[J].IEEE,2002,0-7803-7622-6/02.
[39]H.Farid.Detecting Hidden Messages Using Higher-Order Statistical Models[C].International Conference on Image Processing(ICIP)[A],Rochester,NY,2002.
[40]Shao hui Liu,Hongxun Yao,Wen Gao.Steganalysis Based on Wavelet Texture Analysis and Neural Network[A].Proceedings of the 5th Word Congress on Intelligent Control[C].IEEE,2004:4066-4069.
[41]Siwei Lyu,Hany Farid.Steganalysis Using Higher-Order Image Statistics[J].IEEE Transactions on Information Forensics and Security,2006,1(1):111-118.
[42]Liu Shaohui,Yao Hongxun,Gao Wen.Neural Network Based Steganalysis in Still Images[A].Multimedia and Expo,2003.ICME'03.Proceedings.2003 International Conference[C],2003,2(11):509-12.
[43]Mark T.Hogan,Gu'enol'e C.M.Silvestre and Neil J.Hurley.Performance Evaluation of Blind Steganalysis Classifiers[J].Proc.of SPIE-IS&T Electronic Imaging,2004,5306:58-69.
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