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"The only real way to maintain privacy is to be uninteresting. It may be that privacy is a passing fad."
- Larry Niven
 |
| Photonomous | ||
| A program that strips out the digital noise signature from a picture file. |
In the novel, this handy utility is supplied along with every copy of ParanoidLinux.
| My mailbox overflowed with suggestions from people. They sent me dumps off their phones and their pocket-cameras. Then I got an email from a name I recognized -- Dr Eeevil (three "e"s), one of the prime maintainers of ParanoidLinux.
> I have been watching your Xnet experiment with great interest. Here in Germany, we have much experience with what happens with a government that gets out of control.
> One thing you should know is that every camera has a unique "noise signature" that can be used to later connect a picture with a camera. That means that the photos you're republishing on your site could potentially be used to identify the photographers, should they later be picked up for something else.
> Luckily, it's not hard to strip out the signatures, if you care to. There's a utility on the ParanoidLinux distro you're using that does this -- it's called photonomous, and you'll find it in /usr/bin. Just read the man pages for documentation. It's simple though.
> Good luck with what you're doing. Don't get caught. Stay free. Stay paranoid.
> Dr Eeevil
I de-fingerprintized all the photos I'd posted and put them back up, along with a note explaining what Dr Eeevil had told me, warning everyone else to do the same. We all had the same basic ParanoidXbox install, so we could all anonymize our pictures. There wasn't anything I could do about the photos that had already been downloaded and cached, but from now on we'd be smarter. |
| From Little Brother,
by Cory Doctorow. Published by Tor Teen in 2008 Additional resources -
|
In real life, as far as I know, there is no such thing as photonomous. There really is such a thing as a digital noise signature, however. Every camera differs just slightly from every other camera; the tiny differences or imperfections in the lenses and sensors in the camera leave their mark on each finished image.
Jessica Fridrich, associate professor of electrical and computer engineering at Binghamton University, State University of New York, did some research on this topic and offers these results:
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 camera's 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 isn't 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 virtually ensures 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, Fridrich's lab analyzed 2,700 pictures taken by nine digital cameras and with 100 percent accuracy linked individual images with the camera that took them.
Read more at Binghamton University research links digital images and cameras.
I think I can safely predict the creation of "one-time cameras," digital cameras that are used on only one occasion. Once the photos are taken and uploaded, the camera is destroyed.
Fridrich's 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.
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