视频取证技术研究进展
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摘要
由于近年来多媒体采集设备和影像处理工具的普及和广泛应用,人们可以轻易对图像和视频进行篡改。利用恶意篡改的图像和视频进行敲诈勒索的案件日益增多,判断监控系统拍摄或者网上下载的图像和视频的原始性和真实性成了迫切需要解决的问题。之前的研究工作多集中在图像取证领域,对视频取证的研究近几年刚刚开始。和图像相比,视频数据量大,数据格式复杂,存储压缩因子高,对取证算法的计算要求高;不过,由于视频在编码方式、时空特性、篡改手段上都有着鲜明的特点,视频取证有更为丰富的研究内容和更为广阔的应用前景。研究人员利用视频采集和压缩编码过程中的特性,以及篡改手段带来的痕迹,对视频篡改检测方法进行了相关探索,取得了一些成果。先前的综述文献大都集中在图像取证领域,只有少数细节涉及到视频取证分析,本文对视频取证技术进行了综述。鉴于某些图像取证技术可用于视频单帧图像取证分析,本文第一部分首先介绍了图像取证相关技术如相机参数、压缩和物理几何不一致取证等。接着对已经提出的视频取证技术,按照采集、压缩和篡改方式进行分类,对它们的原理和优缺点进行了综述,并对反取证技术的相关研究工作进行了介绍。第二部分重点介绍视频采集过程以及辨识视频采集设备的一些方法。第三部分对因编码参数、编码标准以及压缩次数等视频编码过程的不同而遗留的痕迹进行了探讨。第四部分将介绍基于检测视频采集和编码痕迹不一致的取证分析方法,以及揭示篡改遗留痕迹的方法。图像视频压缩检测取证方法的发展始终伴随着相应反取证方法的研究,因此第五部分对视频反取证方法做了介绍。视频取证已经逐渐成为一个研究热点,得到越来越多的研究和关注,仍有许多未知的领域等待更加深入的研究和探索。
Digital videos and photographs can be altered rather easily since the broad availability of tools for the acquisition and processing in recent years, and using tampered images and videos to extort and threat becomes more and more serious. All these reasons raise the need to verify whether a multimedia content, which can be acquired by a video surveillance system, downloaded from the internet, or received by a digital TV broadcaster, is original or not. Previous work mainly focuses on image forensics, and it is only in recent years that forensi c experts have begun specific research into video forensics. Compared with image forensics, video forensics have new challenges such as computing power because of the large amount and the complexity of data, and high compression factor; however, video signals have distinctive characteristics such as encoded mode, spatial and temporal characteristics, and ways of tampering giving video forensics a more abundant contents and broader application prospects. Signal processing experts have been investigating video forensic strategies and have made some progress, using the peculiarities of video signals and footprints left by alterations. Previous overview papers mainly address image forensic technology and only a few details are provided about video forensic analysis, so we present an overview of the video forensic techniques that have been proposed in the literature in this paper. Considering each frame as single image and many of image forensic tools can be applied to video signals as well, we first give a preliminary review of image forensics which provides the foundations for analogous techniques targeting video content in Section 1, such as camera artifacts, compression and geometric/physical inconsistencies. Next, we give a survey of video forensic technology focusing on various aspects related to video forensics such as acquisition, compression, and editing operations, and summarize the strengths and weaknesses of each solution. Then we address video acquisition in Section 2, presenting several strategies to identify the device that captured a given video content. Then, we consider the traces left by video coding, which are used to determine, e.g., coding parameters, coding standard, number of multiple compression steps or network footprints in Section 3. Video doctoring is addressed in Section 4, which presents forensic analysis methods based on detecting inconsistencies in acquisition and coding-based footprints, as well as methods that reveal traces left by the forgery itself such as inconsistencies in c ontent and copy-move detection in video. As the design of novel forensic strategies aimed at image and video paralleled by the investigation of corresponding anti-forensic methods, we provide a brief introduction to anti-forensic techniques in Sect ion 5. Video forensics is becoming research focus gradually, receiving more and more attenti on, and still presents many unexplored issues that wait for further study and deeper exploration.
Digital videos and photographs can be altered rather easily since the broad availability of tools for the acquisition and processing in recent years, and using tampered images and videos to extort and threat becomes more and more serious. All these reasons raise the need to verify whether a multimedia content, which can be acquired by a video surveillance system, downloaded from the internet, or received by a digital TV broadcaster, is original or not. Previous work mainly focuses on image forensics, and it is only in recent years that forensi c experts have begun specific research into video forensics. Compared with image forensics, video forensics have new challenges such as computing power because of the large amount and the complexity of data, and high compression factor; however, video signals have distinctive characteristics such as encoded mode, spatial and temporal characteristics, and ways of tampering giving video forensics a more abundant contents and broader application prospects. Signal processing experts have been investigating video forensic strategies and have made some progress, using the peculiarities of video signals and footprints left by alterations. Previous overview papers mainly address image forensic technology and only a few details are provided about video forensic analysis, so we present an overview of the video forensic techniques that have been proposed in the literature in this paper. Considering each frame as single image and many of image forensic tools can be applied to video signals as well, we first give a preliminary review of image forensics which provides the foundations for analogous techniques targeting video content in Section 1, such as camera artifacts, compression and geometric/physical inconsistencies. Next, we give a survey of video forensic technology focusing on various aspects related to video forensics such as acquisition, compression, and editing operations, and summarize the strengths and weaknesses of each solution. Then we address video acquisition in Section 2, presenting several strategies to identify the device that captured a given video content. Then, we consider the traces left by video coding, which are used to determine, e.g., coding parameters, coding standard, number of multiple compression steps or network footprints in Section 3. Video doctoring is addressed in Section 4, which presents forensic analysis methods based on detecting inconsistencies in acquisition and coding-based footprints, as well as methods that reveal traces left by the forgery itself such as inconsistencies in c ontent and copy-move detection in video. As the design of novel forensic strategies aimed at image and video paralleled by the investigation of corresponding anti-forensic methods, we provide a brief introduction to anti-forensic techniques in Sect ion 5. Video forensics is becoming research focus gradually, receiving more and more attenti on, and still presents many unexplored issues that wait for further study and deeper exploration.
引文
[1]黎智辉,王桂强,许小京,等.视频侦查中的影像证据应用[J].北京:刑事技术,2014,(2):42-45.
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[9]Zhang W,Cao X,Zhang J.Detecting photographic composites using shadows[C].IEEE International Conference on Multimedia&Expo,2009:1042-1045.
[10]Conotter V,Boato G,Farid H.Detecting photo manipulation on signs and billboards[C].IEEE International Conference on Image Processing,2010:1741-1744.
[11]Kang L W,Hsu C Y,Chen H W.Feature-based sparse representation for image similarity assessment[J].IEEE International Transactions on Multimedia,2011,13(5):1019-1030.
[12]杜振龙,杨凡,李晓,等.利用SIFT特征的非对称匹配图像拼接盲检测[J].中国图象图形学报,2013,18(4):442-449.
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[14]Amerini I,Caldelli R,Cappellini V.Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification[C].IEEE International Conference on Digital Signal Processing,2009:1-7.
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[16]Wang W,Farid H.Detecting re-projected video[A].Information Hiding,2008:72-86.
[17]Lee J W,Lee M J,Oh T W.Screenshot identification using combing artifact from interlaced video[C].ACM Workshop on Multimedia and Security,2010:49-54.
[18]Bayram S,Sencar H T,Memon N D.Video copy detection based on source device characteristics:a complementary approach to content-based methods[C].ACM International Conference on Multimedia Information Retrieval,2008:435-442.
[19]Li H,Forchhammer S.MPEG2 video parameter and no reference PSNR estimation[A].Picture Coding Symposium,2009:1-4.
[20]Ye S,Sun Q,Chang E C.Detecting digital image forgeries by measuring inconsistencies of blocking artifact[C].IEEE International Conference on Multimedia&Expo,2007:12-15.
[21]Valenzise G.Tagliasacchi M,Tubaro S.Estimating QP and motion vectors in H.264/AVC video from decoded pixels[A].ACM Workshop on Multimedia in Forensics,Security and Intelligence,2010:89-92.
[22]He J,Lin Z,Wang L,et al.Detecting doctored JPEG images via DCT coefficient analysis[A].Computer Science,2006:423-435.
[23]Wang W,Farid H.Exposing digital forgeries in video by detecting double MPEG compression[A].ACM Workshop on Multimedia and Security,2006:37-47.
[24]Bestagini P,Allam A,Milani S,et al.Video codec identification[C].IEEE International Conference on Acoustics,Speech,and Signal Processing,2012:2257-2260.
[25]Reibman A,Vaishampayan V.Quality monitoring of video over a packet network[J].IEEE International Transactions on Multimedia,2004,6(2):327-334.
[26]Naccari M,Tagliasacchi M,Tubaro S.No-reference video quality monitoring for H.264/AVC coded video[J].IEEE International Transactions on Multimedia,2009,11(5):932-946.
[27]Valenzise G,Magni S,Tagliasacch M,et al.No-reference pixel video quality monitoring of channel-induced distortion[J].IEEE Trans.Circuits and Systems for Video Technology,2012,22(4):605-618.
[28]Hsu C T,Hung T Y,Lin C W.Video forgery detection using correlation of noise residue[A].IEEE Workshop on Multimedia Signal Processing,2008:170-174.
[29]Kobayashi M,Okabe T,Sato Y.Detecting forgery from staticscene video based on inconsistency in noise level functions[J].IEEE Trans.Information Forensics and Security,2010,5(4):450-461.
[30]Wang W,Farid H.Exposing digital forgeries in video by detecting double quantization[A].ACM Workshop on Multimedia and Security,2009:39-48.
[31]Wang W,Farid H.Exposing digital forgeries in interlaced and deinterlaced video[J].IEEE Trans.Information Forensics and Security,2007,2(4):238-258.
[32]张明玉.基于“鬼影”的数字视频篡改检测[D].天津:天津大学,2010.
[33]Conotter V,O’Brien J,Farid H.Exposing digital forgeries in ballistic motion[J].IEEE Trans.Information Forensics and Security,2012,7(1):283-296.
[34]Wang W,Farid H.Exposing digital forgeries in video by detecting duplication[A].ACM Workshop on Multimedia and Security,2007:35-42.
[35]Stamm M C,Tjoa S K,Lin W S,et al.Undetectable image tampering through JPEG compression anti-forensics[C].IEEE International Confe rence on Image Processing,2010:2109-2112.
[36]Valenzise G,Nobile V,Tagliasacchi M,et al.Countering jpeg anti-forensics[C].IEEE International Conference on Image Processing,2011:1949-1952.
[37]Stamm M C,Liu K J.Anti-forensics for frame deletion/addition in mpeg video[C].IEEE International Conference on Acoustics,Speech,and Signal Processing,2011:1876-1879.
[2]许磊,郭晶晶,黎智辉.合成不雅视频案件检验1例[J].刑事技术,2014,(4):13,17.
[3]段成阁,倪萍娅,张国臣,等.浅析监控视频鉴定[J].刑事技术,2012,(4):42-44,72.
[4]Chen M,Fridrich J,Goljan M,et al.Determining image origin and integrity using sensor noise[J].IEEE Trans.Information Forensics and Security,2008,3(1):74-90.
[5]Popescu A,Farid H.Exposing digital forgeries in color filter array interpolated images[J].IEEE Trans.Signal Processing,2005,53(10):3948-3959.
[6]Yerushalmy I,Hel-Or H.Digital image forgery detection based on lens and sensor aberration[J].Int J Computer Vision,2001,92(1):71-91.
[7]Lin W S,Tjoa S K,Zhao H V,et al.Digital image source coder forensics via intrinsic fingerprints[J].IEEE Trans.Information Forensics and Security,2009,4(3):460-475.
[8]Johnson M,Farid H.Exposing digital forgeries in complex lighting environments[J].IEEE Trans.Information Forensics and Security,2007,2(3):450-461.
[9]Zhang W,Cao X,Zhang J.Detecting photographic composites using shadows[C].IEEE International Conference on Multimedia&Expo,2009:1042-1045.
[10]Conotter V,Boato G,Farid H.Detecting photo manipulation on signs and billboards[C].IEEE International Conference on Image Processing,2010:1741-1744.
[11]Kang L W,Hsu C Y,Chen H W.Feature-based sparse representation for image similarity assessment[J].IEEE International Transactions on Multimedia,2011,13(5):1019-1030.
[12]杜振龙,杨凡,李晓,等.利用SIFT特征的非对称匹配图像拼接盲检测[J].中国图象图形学报,2013,18(4):442-449.
[13]Kurosawa K,Kuroki K,Saitoh N.CCD fingerprint method identification of a video camera from videotaped images[C].IEEE International Conference on Image Processing,1999,3:537-540.
[14]Amerini I,Caldelli R,Cappellini V.Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification[C].IEEE International Conference on Digital Signal Processing,2009:1-7.
[15]Van Houten W,Geradts Z,Franke K.Verification of video source camera competition[A].Recognizing Patterns in Signals,Speech,Images and Videos,2010:22-28.
[16]Wang W,Farid H.Detecting re-projected video[A].Information Hiding,2008:72-86.
[17]Lee J W,Lee M J,Oh T W.Screenshot identification using combing artifact from interlaced video[C].ACM Workshop on Multimedia and Security,2010:49-54.
[18]Bayram S,Sencar H T,Memon N D.Video copy detection based on source device characteristics:a complementary approach to content-based methods[C].ACM International Conference on Multimedia Information Retrieval,2008:435-442.
[19]Li H,Forchhammer S.MPEG2 video parameter and no reference PSNR estimation[A].Picture Coding Symposium,2009:1-4.
[20]Ye S,Sun Q,Chang E C.Detecting digital image forgeries by measuring inconsistencies of blocking artifact[C].IEEE International Conference on Multimedia&Expo,2007:12-15.
[21]Valenzise G.Tagliasacchi M,Tubaro S.Estimating QP and motion vectors in H.264/AVC video from decoded pixels[A].ACM Workshop on Multimedia in Forensics,Security and Intelligence,2010:89-92.
[22]He J,Lin Z,Wang L,et al.Detecting doctored JPEG images via DCT coefficient analysis[A].Computer Science,2006:423-435.
[23]Wang W,Farid H.Exposing digital forgeries in video by detecting double MPEG compression[A].ACM Workshop on Multimedia and Security,2006:37-47.
[24]Bestagini P,Allam A,Milani S,et al.Video codec identification[C].IEEE International Conference on Acoustics,Speech,and Signal Processing,2012:2257-2260.
[25]Reibman A,Vaishampayan V.Quality monitoring of video over a packet network[J].IEEE International Transactions on Multimedia,2004,6(2):327-334.
[26]Naccari M,Tagliasacchi M,Tubaro S.No-reference video quality monitoring for H.264/AVC coded video[J].IEEE International Transactions on Multimedia,2009,11(5):932-946.
[27]Valenzise G,Magni S,Tagliasacch M,et al.No-reference pixel video quality monitoring of channel-induced distortion[J].IEEE Trans.Circuits and Systems for Video Technology,2012,22(4):605-618.
[28]Hsu C T,Hung T Y,Lin C W.Video forgery detection using correlation of noise residue[A].IEEE Workshop on Multimedia Signal Processing,2008:170-174.
[29]Kobayashi M,Okabe T,Sato Y.Detecting forgery from staticscene video based on inconsistency in noise level functions[J].IEEE Trans.Information Forensics and Security,2010,5(4):450-461.
[30]Wang W,Farid H.Exposing digital forgeries in video by detecting double quantization[A].ACM Workshop on Multimedia and Security,2009:39-48.
[31]Wang W,Farid H.Exposing digital forgeries in interlaced and deinterlaced video[J].IEEE Trans.Information Forensics and Security,2007,2(4):238-258.
[32]张明玉.基于“鬼影”的数字视频篡改检测[D].天津:天津大学,2010.
[33]Conotter V,O’Brien J,Farid H.Exposing digital forgeries in ballistic motion[J].IEEE Trans.Information Forensics and Security,2012,7(1):283-296.
[34]Wang W,Farid H.Exposing digital forgeries in video by detecting duplication[A].ACM Workshop on Multimedia and Security,2007:35-42.
[35]Stamm M C,Tjoa S K,Lin W S,et al.Undetectable image tampering through JPEG compression anti-forensics[C].IEEE International Confe rence on Image Processing,2010:2109-2112.
[36]Valenzise G,Nobile V,Tagliasacchi M,et al.Countering jpeg anti-forensics[C].IEEE International Conference on Image Processing,2011:1949-1952.
[37]Stamm M C,Liu K J.Anti-forensics for frame deletion/addition in mpeg video[C].IEEE International Conference on Acoustics,Speech,and Signal Processing,2011:1876-1879.