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382 points DamonHD | 1 comments | | HN request time: 0s | source
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lynndotpy ◴[] No.43697899[source]
> Years ago it would've required a supercomputer and a PhD to do this stuff

This isn't actually true. You could do this 20 years ago on a consumer laptop, and you don't need the information you get for free from text moving under a filter either.

What you need is the ability to reproduce the conditions the image was generated and pixelated/blurred under. If the pixel radius only encompasses, say, 4 characters, then you only need to search for those 4 characters first. And then you can proceed to the next few characters represented under the next pixelated block.

You can think of pixelation as a bad hash which is very easy to find a preimage for.

No motion necessary. No AI necessary. No machine learning necessary.

The hard part is recreating the environment though, and AI just means you can skip having that effort and know-how.

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cogman10 ◴[] No.43697947[source]
In fact, there was a famous de-censoring that happened because the censoring which happened was a simple "whirlpool" algorithm that was very easy to unwind.

If media companies want to actually censor something, nothing does better than a simple black box.

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rcfox ◴[] No.43698511[source]
> nothing does better than a simple black box

You still need to be aware of the context that you're censoring in. Just adding black boxes over text in a PDF will hide the text on the screen, but might still allow the text to be extracted from the file.

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falcor84 ◴[] No.43698913[source]
Indeed. And famously, using black boxes as a background on individual words in a non-monospaced font is also susceptible to a dictionary attack on an image of the widths of the black boxes.
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snotrockets ◴[] No.43699018[source]
No need for the monospaced requirement - it would reduce the search space, but it's solvable even before this reduction.
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1. fc417fc802 ◴[] No.43699246[source]
The additional leakage provided by non-monospace is rather large. With monospace all you know is the character count.