zlacker

[return to "Image Scrubber: tool for anonymizing photographs taken at protests"]
1. Ansil8+vn[view] [source] 2020-05-31 18:06:15
>>dsr12+(OP)
Some tips to maximise user privacy while deploying this tool:

1) The code, for now, runs locally. This is good. To avoid the possibility of the code being tampered with at a later day (for example, it could be modified to send copies of the image to a server), download the webpage and use the saved copy, not the live copy.

2) Do not use the blur functionality. For maximum privacy, this should be removed from the app entirely. There are _a lot_ of forensic methods to reverse blur techniques.

3) Be weary of other things in the photograph that might identify someone: reflections, shadows, so on.

4) Really a subset of 2 and 3, but be aware that blocking out faces is often times not sufficient to anonymise the subject in the photo. Identifying marks like tattoos, or even something as basic as the shoes they are wearing, can be used to identify the target.

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2. Nightl+Qn[view] [source] 2020-05-31 18:09:34
>>Ansil8+vn
"There are _a lot_ of forensic methods to reverse blur techniques"

Any examples? You can't reverse it if the data is gone.

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3. forgot+lo[view] [source] 2020-05-31 18:14:05
>>Nightl+Qn
The data may still be there, it just looks like it's gone.
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4. okamiu+ep[view] [source] 2020-05-31 18:20:49
>>forgot+lo
Blur is in effect a lowpass filter on the image. The high frequency information is gone. Reconstruction based on domain knowledge, like AI methods etc is unlikely to be able to reconstruct the distinguishing features between people enough to avoid false positives when used to search for similar people.

Then again, maybe groups of people can be associated together, and a poor match is good enough given other clues.

So, much better to be safe than sorry.

I'm not sure if I had a particular good point to make, other than that blurring does remove information that cannot easily be reversed. You can probably make very convincing reconstructions, but they might not look like the original person.

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5. radars+Zs[view] [source] 2020-05-31 18:53:04
>>okamiu+ep
> The high frequency information is gone

diminished in power.

It's only gone if it goes below the quantization threshold. Depends on the filter.

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6. okamiu+xB2[view] [source] 2020-06-01 15:56:15
>>radars+Zs
True. I think the reasonable assumption would be a low-pass filter that removes high frequencies altogether. A gaussian filter wouldn't be a particularly good idea.
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