Child pornographers will soon have a harder time escaping
prosecution thanks to a stunning new technology in development at
Binghamton University, State University of New York, that can
reliably link digital images to the camera with which they were
taken, in much the same way that tell-tale scratches are used by
forensic examiners to link bullets to the gun that fired
them.
The defense in these kind of cases would often be that the images
were not taken by this persons camera or that the images are not
of real children, said Jessica Fridrich, associate professor of
electrical and computer engineering. Sometimes child pornographers
will even cut and paste an image of an adults head on the image of
a child to try to avoid prosecution.
But if it can be shown that the original images were taken by the
persons cell phone or camera, it becomes a much stronger case than
if you just have a bunch of digital images that we all know are
notoriously easy to manipulate.
Fridrich and two members of her Binghamton University research team
Jan Lukas and Miroslav Goljan are coinventors of the new
technique, which can also be used to detect forged images.
The three have applied for two patents related to their technique,
which provides the most robust strategy for digital image forgery
detection to date, even as it improves significantly on the
accuracy of other approaches.
Fridrichs technique is rooted in the discovery by her research
group of this simple fact: Every original digital picture is
overlaid by a weak noise-like pattern of pixel-to-pixel
non-uniformity.
Although these patterns are invisible to the human eye, the unique
reference pattern or fingerprint of any camera can be
electronically extracted by analyzing a number of images taken by a
single camera.
That means that as long as examiners have either the camera that
took the image or multiple images they know were taken by the same
camera, an algorithm developed by Fridrich and her co-inventors to
extract and define the cameras unique pattern of pixel-to-pixel
non-uniformity can be used to provide important information about
the origins and authenticity of a single image.
The limitation of the technique is that it requires either the
camera or multiple images taken by the same camera, and isnt
informative if only a single image is available for analysis.
Like actual fingerprints, the digital noise in original images
is stochastic in nature that is, it contains random variables
which are inevitably created during the manufacturing process of
the camera and its sensors. This virtuallyensures that the noise
imposed on the digital images from any particular camera will be
consistent from one image to the next, even while it is distinctly
different
In preliminary tests, Fridrichs lab analyzed 2,700 pictures taken
by nine digital cameras and with 100 percent accuracy linked
individual images with the camera that took them.
Fridrich, who specializes in all aspects of information hiding in
digital imagery, including watermarking for authentication, tamper
detection, self-embedding, robust watermarking, steganography and
steganalysis, as well as forensic analysis of digital images, says
it is the absence of the expected digital fingerprint in any
portion of an image that provides the most conclusive evidence of
image tampering.
In the near future, Fridrichs technique promises to find
application in the analysis of scanned and video imagery. There it
can be expected to make life more difficult for forgers, or any
others whose criminal pursuits rely on the misuse of digital
images.
We already know law enforcement wants to be able to use this,
Fridrich said. What we have right now is a research tool; its a
raw technology that we will continue to improve.