Multimedia Security and Forensics

8/8/2019 Multimedia Security and Forensics

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Multimedia Security And ForensicsMultimedia Security And ForensicsAuthentication of Digital ImagesAuthentication of Digital Images

Sarah SummersSarah SummersSarah WahlSarah Wahl

CS525 Semester ProjectCS525 Semester Project

Spring 2006Spring 2006


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MotivationMotivation

Seeing is believing or is it?Seeing is believing or is it?


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Easy to be deceivedEasy to be deceived


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GoalsGoals

Identify image tampering methods.Identify image tampering methods.

Assess method

s available for protectingAssess method

s available for protectingimages.images.

Assess image authentication techniques.Assess image authentication techniques.

Identify directions for future work.Identify directions for future work.


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Categories of Image TamperingCategories of Image Tampering

There are three main categories of imageThere are three main categories of image

tampering:tampering:

EnhancingEnhancing

CompositingCompositing

Copy/MoveCopy/Move


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CompositingCompositing

Combining two orCombining two ormore images tomore images to

create a new imagecreate a new image


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CopyCopy--MoveMove

Copying regions ofCopying regions ofthe original imagethe original imageand pasting intoand pasting into

other areasother areas..

The yellow area hasThe yellow area has

been copied

and

been copied

and

moved to concealmoved to concealthe truck.the truck.


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What can be done to protectWhat can be done to protect

digital images?digital images?WatermarkingWatermarking

Fragile watermarksFragile watermarks

SemiSemi--fragile watermarksfragile watermarksSelfSelf--embedding watermarksembedding watermarks

Digital cameras with watermarkingDigital cameras with watermarking

capabilitiescapabilities

Digital Fingerprinting/SignaturesDigital Fingerprinting/Signatures

Digital cameras with fingerprintingDigital cameras with fingerprinting

capabilitiescapabilities


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Digital WatermarkingDigital Watermarking

The basic concept ofdigital watermarkingThe basic concept ofdigital watermarking

an image is that a low level signal isan image is that a low level signal is

placeddirectly into the image data.placeddirectly into the image data.

Any manipulation of the image will impactAny manipulation of the image will impact

the watermark and subsequent retrieval ofthe watermark and subsequent retrieval of

the watermark and examination of itsthe watermark and examination of its

condition will indicate if tampering hascondition will indicate if tampering hasoccurred.occurred.


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Fragile WatermarksFragile Watermarks

Fragile watermarks are designed to detectFragile watermarks are designed to detectevery possible change in pixel values .every possible change in pixel values .

Variety ofTechniques but in most cases,Variety ofTechniques but in most cases,

the watermark is embedded in the leastthe watermark is embedded in the leastsignificant bit (LSB) of the image.significant bit (LSB) of the image.

Advantages: Pick up all imageAdvantages: Pick up all imagemanipulationsmanipulations malicious and nonmalicious and non--maliciousmalicious

Disadvantages: Too sensitiveDisadvantages: Too sensitive


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SemiSemi--Fragile WatermarksFragile Watermarks They are robust, to a certain extent, and are lessThey are robust, to a certain extent, and are less

sensitive to pixel modifications.sensitive to pixel modifications.

Techniques:Techniques:

Divide image into blocks an

dutilize bits from eachDivi

de image into blocks an

dutilize bits from eachblock to calculate a spread spectrum noise like signalblock to calculate a spread spectrum noise like signal

which is combined with DCT coefficients and insertedwhich is combined with DCT coefficients and insertedas a watermark.as a watermark.

Divide image into blocks, construct watermark in DCTDivide image into blocks, construct watermark in DCT

domain from pseudodomain from pseudo--random zerorandom zero--mean unit variancemean unit varianceGaussian numbers, take the inverse DCT and insertGaussian numbers, take the inverse DCT and insertinto the image.into the image.

Advantage: less sensitive than fragile watermarksAdvantage: less sensitive than fragile watermarks


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SelfSelf--EmbeddingEmbedding

Tampered images result in lost information. The previousTampered images result in lost information. The previoustechniques will only detect and localize areas of interesttechniques will only detect and localize areas of interestwhen authentication is carried out.when authentication is carried out.

SelfSelf--embedding allows tamperdetection and recovery ofembedding allows tamperdetection and recovery of

missing information.missing information.

General concept is that the image is embedded in itselfGeneral concept is that the image is embedded in itselfin an encrypted form.in an encrypted form.

Advantage: Potential for original data to be retrieved.Advantage: Potential for original data to be retrieved.

Disadvantage: Tampering with the image can removeDisadvantage: Tampering with the image can removeblocks of the original image making retrieval of contentblocks of the original image making retrieval of contentimpossibleimpossible


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Digital Cameras withDigital Cameras with

WatermarkingC

apabilitiesWatermarkingC

apabilities Watermarking based on secret key, block ID andWatermarking based on secret key, block ID and

content. The image is divided into blocks andcontent. The image is divided into blocks and

each block watermarked using a frequencyeach block watermarked using a frequency

based spread spectrum technique incorporatingbased spread spectrum technique incorporatingthe secret key, block ID and block content.the secret key, block ID and block content.

Image of photographers iris is combined with theImage of photographers iris is combined with the

camera ID, the hash of the original image andcamera ID, the hash of the original image and

otherdetails specific to the camera.otherdetails specific to the camera.


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Digital Fingerprints/SignaturesDigital Fingerprints/Signatures

Based on the concept of public keyBased on the concept of public keyencryption.encryption.

Hashed version of image is encryptedHashed version of image is encryptedusing a private key.using a private key.

Encrypted file provides a uniqueEncrypted file provides a uniquesignature/fingerprint of the image whichsignature/fingerprint of the image which

can be used to authenticate by decryptioncan be used to authenticate by decryptionwith public key.with public key.

Mainly used in transmission of images.Mainly used in transmission of images.


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Digital Cameras withDigital Cameras with

Fingerprinting CapabilitiesFingerprinting Capabilities

Epson Image Authentication System (IAS)Epson Image Authentication System (IAS)

The IAS software in the camera instantlyThe IAS software in the camera instantly

seals the captured

images with anseals the captured

images with aninvisible digital fingerprint.invisible digital fingerprint.

Verification of image is achieved by anyVerification of image is achieved by any

PC with Image Authentication SystemPC with Image Authentication System

software installedsoftware installed


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Authentication TechniquesAuthentication Techniques

Active AuthenticationActive Authentication

Rely on the presence of a watermark orRely on the presence of a watermark orfingerprint.fingerprint.

Require knowle

dge original image

Require knowle

dge original image

Algorithm/key used to embed the watermarkAlgorithm/key used to embed the watermarkor fingerprint.or fingerprint.

Passive AuthenticationPassive Authentication

No requirement of knowledge of originalNo requirement of knowledge of originalimage.image.

Does not rely of presence of watermark orDoes not rely of presence of watermark orfingerprint.fingerprint.


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Passive AuthenticationPassive Authentication

TechniquesTechniques

Detecting CopyDetecting Copy--MoveMove

Detecting Traces ofReDetecting Traces ofRe--samplingsampling

Detecting LightInconsistenciesDetecting LightInconsistencies


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CopyCopy--Move DetectionMove Detection

Original Image Tampered Image

Exact Match Robust Match


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CopyCopy--Move DetectionMove Detection

Original Image Tampered Image PCA Detection


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ReRe--sampling Detectionsampling Detection

Original Image Tampered Image

Periodic pattern in Fourier

Transform of altered region

Fourier Transform of

unaltered region


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Inconsistencies in LightingInconsistencies in Lighting

Genuine ImageGenuine Image

Tampered ImageTampered Image


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Future ResearchFuture Research

Development of a better self embeddingDevelopment of a better self embedding

technique.technique.

Development of an all inclusive passiveDevelopment of an all inclusive passive

authentication technique.authentication technique.


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ConclusionsConclusions

Digital image forgeries can be used toDigital image forgeries can be used todeceive the public and the authorities.deceive the public and the authorities.

They are here to stay.They are here to stay.

Until non destructible/ non removal digitalUntil non destructible/ non removal digitalwatermarks are perfected, passivewatermarks are perfected, passiveauthentication will remain necessary.authentication will remain necessary.

Currently no single passive authenticationCurrently no single passive authenticationtechnique can detect all types ofdigitaltechnique can detect all types ofdigitalforgeries.forgeries.


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ReferencesReferences Hany Farid, Creating and Detecting Doctored and Virtual Images: Implications to TheHany Farid, Creating and Detecting Doctored and Virtual Images: Implications to The

Child Pornography Prevention Act, Technical Report, TR2004Child Pornography Prevention Act, Technical Report, TR2004--518, Dartmouth518, Dartmouth

College, Computer Science.College, Computer Science.

Detection of CopyDetection of Copy--Move Forgery in Digital Images, Jessica Fridrich, David SoukalMove Forgery in Digital Images, Jessica Fridrich, David Soukaland Jan Lukas, Proceedings of Digital Forensic Research Workshop, August 2003,and Jan Lukas, Proceedings of Digital Forensic Research Workshop, August 2003,www.ws.binghamton.edu/fridrich/Research/copymove.pdfwww.ws.binghamton.edu/fridrich/Research/copymove.pdf

Detection of image alterations using semiDetection of image alterations using semi--fragile watermarks, E.T. Lin, C. I.fragile watermarks, E.T. Lin, C. I.Podilchuk, and E.J. Delp,Podilchuk, and E.J. Delp, http://shay.ecn.purdue.edu/~linet/papers/SPIEhttp://shay.ecn.purdue.edu/~linet/papers/SPIE--2000.pdf2000.pdf

SemiSemi--fragile watermarking forTelltale Tamper Proofing and Authenticating, H. H. Kofragile watermarking forTelltale Tamper Proofing and Authenticating, H. H. Koand S. J. Park,and S. J. Park, http://www.hongik.edu/~sjpark/udt/Semihttp://www.hongik.edu/~sjpark/udt/Semi--Fragile%20Watermarking%20for%20Telltale%20Tamper%20Proofing%20and%20A.Fragile%20Watermarking%20for%20Telltale%20Tamper%20Proofing%20and%20A.docdoc

Methods forTamper Detection in Digital Images, Jiri Fridrich, Proc. ACM WorkshopMethods forTamper Detection in Digital Images, Jiri Fridrich, Proc. ACM Workshopon Multimedia and Security, Orlando, FL, October 30on Multimedia and Security, Orlando, FL, October 30--31, 1999, pp. 1931, 1999, pp. 19--23,23,http://www.ws.binghamton.edu/fridrich/Research/acm99.dochttp://www.ws.binghamton.edu/fridrich/Research/acm99.doc

Information Authentication for a Slippery New Age, S. Walton, Dr. Dobbs Journal,Information Authentication for a Slippery New Age, S. Walton, Dr. Dobbs Journal,Vol. 20, No. 4, pp 18Vol. 20, No. 4, pp 18--26, Apr 199526, Apr 1995

Blind Detection of Photomontage using Higher Order Statistics, T. Ng, S. Chang andBlind Detection of Photomontage using Higher Order Statistics, T. Ng, S. Chang andQ. Sun,Q. Sun, http://www.ee.columbia.edu/~qibin/papers/qibin2004_iscas_1.pdfhttp://www.ee.columbia.edu/~qibin/papers/qibin2004_iscas_1.pdf


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References (continued)References (continued) A New Fingerprinting Method for Digital Images, V. Fotopoulos and A. N. Skodras,A New Fingerprinting Method for Digital Images, V. Fotopoulos and A. N. Skodras,

http://www.upatras.gr/ieee/skodras/pubs/anshttp://www.upatras.gr/ieee/skodras/pubs/ans--c35.pdfc35.pdf

Mehdi Kharrazi, Husrev T. Sencar andNasir Memon, Blind Source CameraMehdi Kharrazi, Husrev T. Sencar andNasir Memon, Blind Source CameraIdentification, International Conference on Image Processing, 2004, ICIP04, VolumeIdentification, International Conference on Image Processing, 2004, ICIP04, Volume1, 241, 24--27 Oct. 2004, pp. 70927 Oct. 2004, pp. 709 --712712

Rotation, Scale andTranslation Invariant Digital Image Watermarking, J.J.K.Rotation, Scale andTranslation Invariant Digital Image Watermarking, J.J.K.ORuanaidh andT. Pun, Proceedings of the ICIP, VOl. 1, pp 536ORuanaidh andT. Pun, Proceedings of the ICIP, VOl. 1, pp 536--539, Santa Barbara,539, Santa Barbara,

California, Oct 1997.California, Oct 1997.

Secure Digital Camera, Paul Blythe and Jessica Fridrich,Secure Digital Camera, Paul Blythe and Jessica Fridrich,http://www.dfrws.org/2004/bios/day3/D3http://www.dfrws.org/2004/bios/day3/D3--lyth_Secure_Digital_Camera.pdflyth_Secure_Digital_Camera.pdf

Alin C. Popescu and Hany Farid, Exposing Digital Forgeries in Color Filter ArrayAlin C. Popescu and Hany Farid, Exposing Digital Forgeries in Color Filter ArrayInterpolatedImages, IEEE Transactions on Signal Processing, Vol. 53, Issue 10, PartInterpolatedImages, IEEE Transactions on Signal Processing, Vol. 53, Issue 10, Part2, October 2005, pp 39482, October 2005, pp 3948--39593959

Epson's Image Authentication fordigicams,Epson's Image Authentication fordigicams,http://www.dpreview.com/new/9904/99040501epson.asphttp://www.dpreview.com/new/9904/99040501epson.asp

When is Seeing Believing, W. J. Mitchell, Scientific American, pp. 44When is Seeing Believing, W. J. Mitchell, Scientific American, pp. 44 --49, February49, February1994.1994.


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References (continued)References (continued) Exposing digital forgeries by detecting inconsistencies in lighting by M. K. JohnsonExposing digital forgeries by detecting inconsistencies in lighting by M. K. Johnson

and H. Farid, ACM Multimedia and Security Workshop, New York, NY, 2005,and H. Farid, ACM Multimedia and Security Workshop, New York, NY, 2005,http://www.cs.dartmouth.edu/~farid/publications/acm05.pdfhttp://www.cs.dartmouth.edu/~farid/publications/acm05.pdf

Exposing Digital Forgeries by Detecting Traces ofReExposing Digital Forgeries by Detecting Traces ofRe--sampling, A. C. Popescu andsampling, A. C. Popescu andH. Farid, IEEE Transactions on Signal Processing, 53(2):758H. Farid, IEEE Transactions on Signal Processing, 53(2):758--767, 2005,767, 2005,http://www.cs.dartmouth.edu/~farid/publications/sp05.pdfhttp://www.cs.dartmouth.edu/~farid/publications/sp05.pdf

Exposing digital forgeries by detecting duplicated image regions, A. C. Popescu andExposing digital forgeries by detecting duplicated image regions, A. C. Popescu and

H. Farid,T

echnicalR

eport 2004H. Farid,T

echnicalR

eport 2004--515, Dartmouth College,515, Dartmouth College,http://www.ists.dartmouth.edu/library/trhttp://www.ists.dartmouth.edu/library/tr--20042004--515.pdf515.pdf

A Tutorial on Principal Components Analaysis, Lindsay I. SmithA Tutorial on Principal Components Analaysis, Lindsay I. Smithhttp://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.pdfhttp://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf

Automatic Estimation of the Projected Light Source Direction, P. Nillius and j.Automatic Estimation of the Projected Light Source Direction, P. Nillius and j. O.O.Eklundh, Proceddings of the IEEE Computer Science Conference on ComputerEklundh, Proceddings of the IEEE Computer Science Conference on Computer

Vision and Pattern Recognition, 2001Vision and Pattern Recognition, 2001

Protection of Digital Images Using Self Embedding, J. Fridrich and M. Goljan,Protection of Digital Images Using Self Embedding, J. Fridrich and M. Goljan,Symposium on Content Security and Data Hiding in Digital MediaSymposium on Content Security and Data Hiding in Digital Media, New Jersey, New JerseyInstitute ofTechnology, May 14, 1999,Institute ofTechnology, May 14, 1999,http://www.ws.binghamton.edu/fridrich/Research/nj_may14.dochttp://www.ws.binghamton.edu/fridrich/Research/nj_may14.doc

A Model forImage Splicing, T. Ng and S. Chang, ICIP '04. International ConferenceA Model forImage Splicing, T. Ng and S. Chang, ICIP '04. International Conferenceon Image Processing,. Volume 2,on Image Processing,. Volume 2, 2424--27 Oct. 2004 Page(s):116927 Oct. 2004 Page(s):1169 -- 1172 Vol.21172 Vol.2

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