Multimedia Security And Forensics

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Multimedia Security And Forensics

• Authentication of Digital Images

CS525 Semester Project Spring 2006
Sarah Summers Sarah Wahl
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MotivationSeeing is believing or is it?
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Easy to be deceived
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Goals

• Identify image tampering methods.
• Assess methods available for protecting images.
• Assess image authentication techniques.
• Identify directions for future work.

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Categories of Image Tampering

• There are three main categories of image
  tampering
• Enhancing
• Compositing
• Copy/Move

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Enhancing

• Changing the color of objects
• Changing the weather conditions
• Blurring out objects

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Compositing
Combining two or more images to create a new
image
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Copy-Move

• Copying regions of the original image and pasting
  into other areas.
• The yellow area has been copied and moved to
  conceal the truck.

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What can be done to protect digital images?

• Watermarking
• Fragile watermarks
• Semi-fragile watermarks
• Self-embedding watermarks
• Digital cameras with watermarking capabilities
• Digital Fingerprinting/Signatures
• Digital cameras with fingerprinting capabilities

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Digital Watermarking

• The basic concept of digital watermarking an
  image is that a low level signal is placed
  directly into the image data.
• Any manipulation of the image will impact the
  watermark and subsequent retrieval of the
  watermark and examination of its condition will
  indicate if tampering has occurred.

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Fragile Watermarks

• Fragile watermarks are designed to detect every
  possible change in pixel values .
• Variety of Techniques but in most cases, the
  watermark is embedded in the least significant
  bit (LSB) of the image.
• Advantages Pick up all image manipulations
  malicious and non-malicious
• Disadvantages Too sensitive

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Semi-Fragile Watermarks

• They are robust, to a certain extent, and are
  less sensitive to pixel modifications.
• Techniques
• Divide image into blocks and utilize bits from
  each block to calculate a spread spectrum noise
  like signal which is combined with DCT
  coefficients and inserted as a watermark.
• Divide image into blocks, construct watermark in
  DCT domain from pseudo-random zero-mean unit
  variance Gaussian numbers, take the inverse DCT
  and insert into the image.
• Advantage less sensitive than fragile watermarks

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Self-Embedding

• Tampered images result in lost information. The
  previous techniques will only detect and localize
  areas of interest when authentication is carried
  out.
• Self-embedding allows tamper detection and
  recovery of missing information.
• General concept is that the image is embedded in
  itself in an encrypted form.
• Advantage Potential for original data to be
  retrieved.
• Disadvantage Tampering with the image can remove
  blocks of the original image making retrieval of
  content impossible

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Digital Cameras with Watermarking Capabilities

• Watermarking based on secret key, block ID and
  content. The image is divided into blocks and
  each block watermarked using a frequency based
  spread spectrum technique incorporating the
  secret key, block ID and block content.
• Image of photographers iris is combined with the
  camera ID, the hash of the original image and
  other details specific to the camera.

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Digital Fingerprints/Signatures

• Based on the concept of public key encryption.
• Hashed version of image is encrypted using a
  private key.
• Encrypted file provides a unique
  signature/fingerprint of the image which can be
  used to authenticate by decryption with public
  key.
• Mainly used in transmission of images.

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Digital Cameras with Fingerprinting Capabilities

• Epson Image Authentication System (IAS)
• The IAS software in the camera instantly seals
  the captured images with an invisible digital
  fingerprint.
• Verification of image is achieved by any PC with
  Image Authentication System software installed

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Authentication Techniques

• Active Authentication
• Rely on the presence of a watermark or
  fingerprint.
• Require knowledge original image
• Algorithm/key used to embed the watermark or
  fingerprint.
• Passive Authentication
• No requirement of knowledge of original image.
• Does not rely of presence of watermark or
  fingerprint.

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Passive Authentication Techniques

• Detecting Copy-Move
• Detecting Traces of Re-sampling
• Detecting Light Inconsistencies

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Copy-Move Detection
Original Image
Tampered Image
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Copy-Move Detection
Original Image
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Re-sampling Detection
Original Image
Tampered Image
Periodic pattern in Fourier Transform of altered
region
Fourier Transform of unaltered region
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Inconsistencies in Lighting
Tampered Image
Genuine Image
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Future Research

• Development of a better self embedding technique.
• Development of an all inclusive passive
  authentication technique.

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Conclusions

• Digital image forgeries can be used to deceive
  the public and the authorities.
• They are here to stay.
• Until non destructible/ non removal digital
  watermarks are perfected, passive authentication
  will remain necessary.
• Currently no single passive authentication
  technique can detect all types of digital
  forgeries.

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References

• Hany Farid, Creating and Detecting Doctored and
  Virtual Images Implications to The Child
  Pornography Prevention Act, Technical Report,
  TR2004-518, Dartmouth College, Computer Science.
• Detection of Copy-Move Forgery in Digital Images,
  Jessica Fridrich, David Soukal and Jan Lukas,
  Proceedings of Digital Forensic Research
  Workshop, August 2003, www.ws.binghamton.edu/frid
  rich/Research/copymove.pdf
• Detection of image alterations using semi-fragile
  watermarks, E.T. Lin, C. I. Podilchuk, and E.J.
  Delp, http//shay.ecn.purdue.edu/linet/papers/SPI
  E-2000.pdf
• Semi-fragile watermarking for Telltale Tamper
  Proofing and Authenticating, H. H. Ko and S. J.
  Park, http//www.hongik.edu/sjpark/udt/Semi-Fragi
  le20Watermarking20for20Telltale20Tamper20Proo
  fing20and20A.doc
• Methods for Tamper Detection in Digital Images,
  Jiri Fridrich, Proc. ACM Workshop on Multimedia
  and Security, Orlando, FL, October 30-31, 1999,
  pp. 19-23, http//www.ws.binghamton.edu/fridrich/R
  esearch/acm99.doc
• Information Authentication for a Slippery New
  Age, S. Walton, Dr. Dobbs Journal, Vol. 20, No.
  4, pp 18-26, Apr 1995
• Blind Detection of Photomontage using Higher
  Order Statistics, T. Ng, S. Chang and Q. Sun,
  http//www.ee.columbia.edu/qibin/papers/qibin2004
  _iscas_1.pdf

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References (continued)

• A Digital Watermark, R. van Schyndel, A. Tirkel
  and C. Osborne , Proceedings of the IEEE
  International Conference on Image Processing,
  vol. 2, pp. 86-90, Austin, Texas, November 1994
  http//goanna.cs.rmit.edu.au/ronvs/papers/ICIP94.
  PDF
• A Watermark for Image Integrity and Ownership
  Verification, P. Wong, ISTs 1998 Image
  Processing, Image Quality, Image Capture, Systems
  Conference, Portland, Oregon, May 1998, pp. 374
  379
• An Invisible Watermarking Technique for Image
  Verification, M. Yeung and F. Mintzer, Proc.
  ICIP97, Santa Barbara, California 1997
• Image watermarking for tamper detection, Jiri
  Fridrich, Proc. ICIP '98, Chicago, Oct 1998,
  http//www.rl.af.mil/programs/shid/downloads/icip9
  8_434.pdf
• Methods for Detecting Changes in Digital Images,
  J. Fridrich, Proc. of The 6th IEEE International
  Workshop on Intelligent Signal Processing and
  Communication Systems (ISPACS'98), Melbourne,
  Australia, 4-6 November 1998, pp. 173177,
  http//www.ws.binghamton.edu/fridrich/Research/isp
  acs.doc
• A Robust Content Based Digital Signature for
  Image Authentication, M. Schneider and S. Chang,
  Proceedings of the International Conference on
  Image Processing, 1996, Volume 3, Issue , 16-19
  Sep 1996 Page(s)227 - 230

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References (continued)

• A New Fingerprinting Method for Digital Images,
  V. Fotopoulos and A. N. Skodras,
  http//www.upatras.gr/ieee/skodras/pubs/ans-c35.pd
  f
• Mehdi Kharrazi, Husrev T. Sencar and Nasir Memon,
  Blind Source Camera Identification, International
  Conference on Image Processing, 2004, ICIP04,
  Volume 1, 24-27 Oct. 2004, pp. 709 -712
• Rotation, Scale and Translation Invariant Digital
  Image Watermarking, J.J.K. ORuanaidh and T.
  Pun, Proceedings of the ICIP, VOl. 1, pp 536-539,
  Santa Barbara, California, Oct 1997.
• Secure Digital Camera, Paul Blythe and Jessica
  Fridrich, http//www.dfrws.org/2004/bios/day3/D3-l
  yth_Secure_Digital_Camera.pdf
• Alin C. Popescu and Hany Farid, Exposing Digital
  Forgeries in Color Filter Array Interpolated
  Images, IEEE Transactions on Signal Processing,
  Vol. 53, Issue 10, Part 2, October 2005, pp
  3948-3959
• Epson's Image Authentication for digicams,
  http//www.dpreview.com/new/9904/99040501epson.asp
  
• When is Seeing Believing, W. J. Mitchell,
  Scientific American, pp. 44 -49, February 1994.

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References (continued)

• Exposing digital forgeries by detecting
  inconsistencies in lighting by M. K. Johnson and
  H. Farid, ACM Multimedia and Security Workshop,
  New York, NY, 2005, http//www.cs.dartmouth.edu/f
  arid/publications/acm05.pdf
• Exposing Digital Forgeries by Detecting Traces of
  Re-sampling, A. C. Popescu and H. Farid, IEEE
  Transactions on Signal Processing, 53(2)758-767,
  2005, http//www.cs.dartmouth.edu/farid/publicati
  ons/sp05.pdf
• Exposing digital forgeries by detecting
  duplicated image regions, A. C. Popescu and H.
  Farid, Technical Report 2004-515, Dartmouth
  College, http//www.ists.dartmouth.edu/library/tr-
  2004-515.pdf
• A Tutorial on Principal Components Analaysis,
  Lindsay I. Smith http//csnet.otago.ac.nz/cosc453/
  student_tutorials/principal_components.pdf
• Automatic Estimation of the Projected Light
  Source Direction, P. Nillius and j. O. Eklundh,
  Proceddings of the IEEE Computer Science
  Conference on Computer Vision and Pattern
  Recognition, 2001
• Protection of Digital Images Using Self
  Embedding, J. Fridrich and M. Goljan, Symposium
  on Content Security and Data Hiding in Digital
  Media, New Jersey Institute of Technology, May
  14, 1999, http//www.ws.binghamton.edu/fridrich/Re
  search/nj_may14.doc
• A Model for Image Splicing, T. Ng and S. Chang,
  ICIP '04. International Conference on Image
  Processing,. Volume 2,  24-27 Oct. 2004
  Page(s)1169 - 1172 Vol.2