I am introducing the Quick Recognition (QR) Act, which requires ICE and CBP officers to wear uniforms featuring QR codes. When scanned, the code would generate a digital ID displaying the officer’s name, badge number, and law enforcement agency.
ICE should be unmasked both physically and digitally.
Even if the QR codes were useful (they aren’t), they can just paint a couple of random squares by hand and the QR code is useless. And no one can tell.
If I’m reading this correctly (I am not knowledgeable on this topic) this seems to only be about part of the code being obscured or missing, but doesn’t really say much about what filling in false squares would do. If some of those squares were in the sections that it uses to calculate what is missing/error correction, and it reads those false squares as part of it, I imagine it could successfully fuck it up if it was done well enough. Maybe it’s actually much harder to do that than it seems, idk. Otherwise, all they’d have to do is fuck with it enough to pass the 30% threshold.
The ability to correct generally means the amount of squares that can have their value flipped (bit error) without changing the message. This can be changing white -> black or black -> white with identical results. If you want to know more about how it works, the article it links about Reed-Solomon error correction goes into more detail about the algorithm.
Still not a good way to solve this issue, but QR codes (and other codes like it) are ubiquitous for good reason.
Thank you for the explanation. A lot of the maths goes over my head, but your posts and articles have helped me understand how they work a bit better and answered a long-standing question I had.
Even if the QR codes were useful (they aren’t), they can just paint a couple of random squares by hand and the QR code is useless. And no one can tell.
QR codes have built in redundancy and can have a not insignificant amount of damage, from 7% to 30% depending on variant. https://en.wikipedia.org/wiki/QR_code#Error_correction
If I’m reading this correctly (I am not knowledgeable on this topic) this seems to only be about part of the code being obscured or missing, but doesn’t really say much about what filling in false squares would do. If some of those squares were in the sections that it uses to calculate what is missing/error correction, and it reads those false squares as part of it, I imagine it could successfully fuck it up if it was done well enough. Maybe it’s actually much harder to do that than it seems, idk. Otherwise, all they’d have to do is fuck with it enough to pass the 30% threshold.
The ability to correct generally means the amount of squares that can have their value flipped (bit error) without changing the message. This can be changing white -> black or black -> white with identical results. If you want to know more about how it works, the article it links about Reed-Solomon error correction goes into more detail about the algorithm.
Still not a good way to solve this issue, but QR codes (and other codes like it) are ubiquitous for good reason.
Thank you for the explanation. A lot of the maths goes over my head, but your posts and articles have helped me understand how they work a bit better and answered a long-standing question I had.