Take a computer screen with a full wash of R, G, or B. Sync the RGB display with your 2FA token, but run it at 15FPS instead of one code per minute.
Point the monitor at the wall, or desk, or whatever. Notice the radiosity and diffuse light scattering on the wall (and on the desk, and on the reflection on the pen cap, and on their pupils).
Now you can take a video that was purported to be taken at 1:23pm at $LOCATION and validate/reconstruct the expected "excess" RGB data and then compare to the observed excess RGB data.
What they say they've done as well is to not just embed a "trace" of expected RGB values at a time but also a data stream (eg: a 1FPS PNG) which kindof self-authenticates the previous second of video.
Obviously it's not RGB, but "noise" in the white channels, and not a PNG, but whatever other image compression they've figured works well for the purpose.
In the R, G, B case you can imagine that it's resistant (or durable through) most edits (eg: cuts, reordering), and it's interesting they're talking about detecting if someone has photoshopped in a vase full of flowers to the video (because they're also encoding a reference video/image in the "noise stream").
Take a computer screen with a full wash of R, G, or B. Sync the RGB display with your 2FA token, but run it at 15FPS instead of one code per minute.
Point the monitor at the wall, or desk, or whatever. Notice the radiosity and diffuse light scattering on the wall (and on the desk, and on the reflection on the pen cap, and on their pupils).
Now you can take a video that was purported to be taken at 1:23pm at $LOCATION and validate/reconstruct the expected "excess" RGB data and then compare to the observed excess RGB data.
What they say they've done as well is to not just embed a "trace" of expected RGB values at a time but also a data stream (eg: a 1FPS PNG) which kindof self-authenticates the previous second of video.
Obviously it's not RGB, but "noise" in the white channels, and not a PNG, but whatever other image compression they've figured works well for the purpose.
In the R, G, B case you can imagine that it's resistant (or durable through) most edits (eg: cuts, reordering), and it's interesting they're talking about detecting if someone has photoshopped in a vase full of flowers to the video (because they're also encoding a reference video/image in the "noise stream").
No, unsafe-yt