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Adversarial image attacks are no joke

unite.ai

81–90 of 196 posts

Re: Adversarial image attacks are no joke

#81
post #63
post #61

Earlier quoted context omitted.

1 and 2 are almost always going to be impossible in the US due to the first amendment (this is a feature not a bug) 3 doesn't seem crazy, but it would practically end up with caps, which might not be what you're looking for 4 This both: seems possible, and will basically never happen due to cost in every little jurisdiction

Defacing property is not free speech...?

Just stand in view holding the image on a poster board.

Re: Adversarial image attacks are no joke

#82
The key point I see in this is that, given the current ecosystem, attacks are systemic. Plus, given the nature of ML training and datasets, it's expensive to bug fix an attack, if it's even possible.

This right here is the real underlying long term danger:

> the most popular CV datasets are so embedded in development cycles around the world as to resemble software more than data; software that often hasn’t been notably updated in years

Re: Adversarial image attacks are no joke

#84

Earlier quoted context omitted.

> For example, consider the case of pasting a sticker on a speed limit sign that causes Teslas to swerve off the road. If your vision system can be caused to swerve off a road by a sticker then maybe it shouldn't be used?

I bet I could cause a significant fraction of human vision systems to get in a crash with a well placed sticker. I'd replace " ".

These attempts to imply a broad equivalence between current machine vision and human capabilities do not hold up under a modicum of scrutiny.

Humans have well-developed models of how things should be, can detect when things seem wrong, and come up with ways to address the apparent anomaly (including taking steps to investigate and evaluate the situation.)

Humans do not always use these capabilities well, but they have them, while similar capabilities are at best rudimentary and fragile in current AI. The premise of this article is that these capabilities will not come easy.

Re: Adversarial image attacks are no joke

#85

Earlier quoted context omitted.

I bet I could cause a significant fraction of human vision systems to get in a crash with a well placed sticker. I'd replace " ".

There are multiple reasons for signs to have different shapes, sizes, and colors, and this is one of them. An orange diamond "detour" sign isn't easily confused for a smaller rectangle "one way" sign. Additionally, there should always be two large "do not enter" plus two large red "wrong way" signs that are visible to a driver from in the intersection before turning. Something as simple as tape or other coverings on…

Some people key off the shape enough that they wouldn't follow a wrongly-shaped detour sign, so you wouldn't fool everyone, but you'd absolutely fool a lot of people. I expect I'd be one of them.

Re: Adversarial image attacks are no joke

#86

It seems to me theres a difference between attacks that carefully craft an image that slips through the cracks, and an attack that basically exploits the fact that without context, it's hard to figure out what single item is important. If I took a picture of a conch shell on top of my keyboard and sent it to someone, no one would think I was just showing off my keyboard! They'd assume, correctly, that my desk was a m…

I don't think that the word 'train' should be used for these systems. We feed then reams of data and effectively cull the ones that don't work but the critical problem is that we judge the effectiveness of an ML system and we actually do know what the ML systems is supposed to be looking for. We feed a system a series of images of bikes and then select the ones that can pick out a bike but we don't know how the bike…

Thank you for an accurate ELI5 description of the human visual system. Dunno what this “ML” is, I assume it’s some part of the brain?

It’s too bad you can’t analyze brains like you can with neural networks. It’s trivial to visualize filters and feature maps or to create heatmaps showing which pixels (shadow shapes?) in a specific image affect the classification output and why (contrasting color?).

Re: Adversarial image attacks are no joke

#87
post #7

As somebody who works on computer vision, my general take on these things is that adversarial examples are like poison. It would be fairly easy to add poison to a water supply or the air intake of a large building and kill a large number of people. This rarely happens though. It's ok that water sources, buildings, and people aren't completely immune to poison. The safety requirement isn't that poison can't hurt. Inst…

> For example, consider the case of pasting a sticker on a speed limit sign that causes Teslas to swerve off the road. If your vision system can be caused to swerve off a road by a sticker then maybe it shouldn't be used?

Turn a temporary road sign for 30 speed-limit into a 80 speed-limit with some black-tape (I have already seen it done when people were angry to be fined by speed-detector for a few excess km/h, (or just for the lulz) ). It probably won't fool humans, but it's an edge case that a self-driving car may ignore.

Re: Adversarial image attacks are no joke

#88
post #53

Earlier quoted context omitted.

You put too much faith in humans. Things like stop sign removal have caused deaths in the past. https://www.nytimes.com/1997/06/21/us/3-are-sentenced-to-15-...

Humans are not so bad as drivers. Your example is an event from over 2 decades ago and was deemed newsworthy. Humans drive in all kinds of conditions but death rate is about 1 per 100 million miles driven. A search reveals crashes to be on the order of hundreds of collisions per 100 million miles driven. Age, country, intoxication level, road design and laws, road and environmental conditions also play a major role s…

I will go further and say that almost everytime there is an accident the driver is somehow impaired. Lack of sleep, drugs, illness (old age included, mental disease), poor judgement (young age included, emotional distress)

Humans are surprisingly good at driving under normal conditions.

Re: Adversarial image attacks are no joke

#89
post #64

Earlier quoted context omitted.

What you are proposing are what I think would be called a security theater. It gives the illusion of security, but they would absolutely not deter a determined threat actor. The only reason that the water supply isn't poisoned is it's unpractical for a single person to conduct the whole exploit chain: Construct the poison in enough quantities, gain access to facilities supplying the water, and actually throwing the c…

> It gives the illusion of security, but they would absolutely not deter a determined threat actor. Sure. And the threat of jail/imprisonment doesn't deter determined murderer's. It doesn't mean we shouldn't put deterrents.

>It doesn't mean we shouldn't put deterrents.

GP doesn't say we shouldn't, but rather that it's not good enough.

Re: Adversarial image attacks are no joke

#90
post #78

Earlier quoted context omitted.

What you are proposing are what I think would be called a security theater. It gives the illusion of security, but they would absolutely not deter a determined threat actor. The only reason that the water supply isn't poisoned is it's unpractical for a single person to conduct the whole exploit chain: Construct the poison in enough quantities, gain access to facilities supplying the water, and actually throwing the c…

Construct the poison in enough quantities, gain access to facilities supplying the water, and actually throwing the compound in it. Gaining access is rather easy. You can easily fly drones over most of reservoirs and dump whatever you want into them. Making strong poisons is also relatively easy, eg. dimethylmercury can be easily synthesized by any chemistry graduate.

You can just pump it back into the municipal water supply from the comfort of your own home (or better yet, someone else’s). You may need to work around a backflow preventer but that’s not too difficult.
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