Digital Image Forensics Through the Use of Noise Reference Patterns

As result of the growing use of digital cameras, methods to identify an image's origin quickly, reliably, and inexpensively are needed. By designing and implementing methods for mitigating or "attacking " forensic features in the images, the robustness of various forensic identification techniques can be analyzed. The objective of this research was to see if drastically modified images could still be identified using a camera’s defects in the form of a reference noise pattern. Experimental data has been gathered using several digital cameras and has been placed in an image database to organize and manage the gathered experimental data. Various types of filters, including blurring, weighted blurring, sharpening, histogram equalization, and pseudo-random noise filters, have been implemented and used to process various images. These images were then used to see if the image's source camera is still identifiable after attacking the image. A reference pattern is found by averaging the noise pattern found in multiple images obtained from the same camera. This intrinsic signature of the camera can be used to correlate with a noise pattern of an image with an unknown origin. If the patterns are similar, and the correlation is above a certain threshold, the camera containing that particular reference pattern is the source camera. All images ’ source camera were identified correctly, and except for a few exceptions, most correlation values for attacked images were lower, and therefore had less similar noise patterns than the original images’. Introduction and Method