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As an example, take a photo with a relatively new digital camera and open the JPG up with an EXIF reader. In all likelihood, you'll see GPS coordinates, the exa
by dkulchenko 14y ago
As an example, take a photo with a relatively new digital camera and open the JPG up with an EXIF reader. In all likelihood, you'll see GPS coordinates, the exact time you took the picture, along with the unique identifier of your camera.
See http://en.wikipedia.org/wiki/Exchangeable_image_file_format#Privacy_and_security http://en.wikipedia.org/wiki/Exchangeable_image_file_format#....
- Sniffnoy 14y agoThat's surely not what kijin was referring to; that can easily be stripped out. Rather there's the problem of being able to determine location purely from the picture itself -- a picture contains a lot more information than just the particular thing you intend to point out in it.
- rwmj 14y agoEven if you scrub the EXIF data (which you absolutely should do of course) remember that it's likely possible to identify if you took a particular photograph with a particular device. That isn't a danger that you'll be identified from the photo, but it prevents plausible denial at a later date. https://www.schneier.com/blog/archives/2006/04/digital_cameras.html https://www.schneier.com/blog/archives/2006/04/digital_camer...
- rorrr 14y agoThis can be easily overcome by adding random noise.
- Dylan16807 14y agoRandom noise only means you need more samples; it can't block a consistent pattern.
- rorrr 14y agoYou can add a consistent random pattern.
- Dylan16807 14y agoYou need a method that can't be distinguished from the native pattern. How much trust do you want to put in your algorithm being invulnerable to future analysis?
- roguecoder 14y agoblur and threshold.