1. Forgery & Forensics Hany Farid ACM Proceedings of the 8th Workshop on Multimedia and Security, Sep. 2006

2. Image Tampering Digital Tampering: Compositing. Morphing. Re-touching. Enhancing. Computer graphics. Painted.

3. Forensics Forensic science, the application of a broad spectrum of sciences to answer questions of interest to the legal system. Digital forensics, the application of the scientific method to digital media in order to establish factual information for judicial review.

4. Discussion The problem of detecting digital forgeries is a complex one with no universally applicable solution. Reliable forgery detection should be approached from multiple directions.

5. Exposing Digital Forgeries in Scientific Images In at least one journal, it is estimated that as many as 20% of accepted manuscripts contain figures with inappropriate manipulations, and 1% with fraudulent manipulations.

6. Image Manipulation Action of each manipulation scheme: Deletion, (a). A band was erased. Healing, (b). Several bands were removing using Photoshop ’ s “ healing brush. ” Duplication, (c). A band was copied and pasted into a new location.

7. Image Manipulation Effect of each manipulation scheme: Deletion. Remove small amounts of noise that are present through the dark background of the image. Healing. Disturb the underlying spatial frequency (texture). Duplication. Leave behind an obvious statistical pattern – two regions in the image are identical. Formulate the problem of detecting each of these statistical patterns as an image segmentation problem.

8. Image Segmentation: Texture For healing. I g ( ． ): the magnitude of the image gradient at a given pixel.

9. Image Segmentation: Texture s d ( ． ): 1D deravative filter. [0.0187 0.1253 0.1930 0.0 −0.1930 −0.1253 −0.0187] p ( ． ): low-pass filter. [0.0047 0.0693 0.2454 0.3611 0.2454 0.0693 0.0047]

10. Automatic Detection