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Representing SHA-256 Hashes as Avatars

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Re: Representing SHA-256 Hashes as Avatars

#31

Post by ianopolous »

raphlinus wrote: post #19

I still like snowflakes for this: https://levien.com/snowflake-explain.html is a half-finished blog post explaining the motivation and algorithm I came up with. I never did careful user testing, but suspect that the answer would be that some people can reliably distinguish the patterns, others won't be able to. In any case, there are a lot of variations on this "visual hash" idea, including the original fractal one,…

This is a great idea! Trying random ones, I couldn't find two I thought looked confusable.

Re: Representing SHA-256 Hashes as Avatars

#32

Post by adzm »

nemo1618 wrote: post #20

The problem with hash avatars in general is that people want to use them for identity verification -- and humans are wired to do so automatically -- but technologically, they cannot provide this. The space of possible avatars (2^256, in this case) is far, far larger than the number of distinct objects that humans can distinguish between. Which means that there will invariably be "collisions:" two avatars that are not…

On a related note, I've been experimenting with using a simple word list (like the eff diceware list) to generate strings of words encoding data. Trickiest part is figuring out how to encode padding, and the eventual size of the word list, and how complicated the final solution should be (eg using word lists that are not even binary numbers and leftover bits and all that). The diceware word list is nice since the words are not ambiguous and don't have homophones.

I assumed there would be existing implementations of something similar but have not found one that fits criteria other than some that use very small word lists. Diceware has 7776 words and pushing that to 8192 should be feasible and is a bit easier to work with.

Re: Representing SHA-256 Hashes as Avatars

#33

Post by sva_ »

nemo1618 wrote: post #24
sva_ wrote: post #23

Earlier quoted context omitted.

> The space of possible avatars (2^256, in this case) is far, far larger than the number of distinct objects that humans can distinguish between. That sounds intriguing to me. Are you aware of any research into this?

To be honest, I have no idea how many distinct objects humans can distinguish between, but I am 99% confident that it is fewer than 2^128, much less 2^256. I suppose it's a somewhat nuanced question, though. For example, if I were shown every avatar in sequence, I'm quite sure I would always notice the "diff" between two consecutive avatars. But the bar that I have in mind is much, much higher: given a sequence of av…

Yeah, I should've been more clear. There's no doubt that humans can't distinguish/memorize 2^256 abstract shapes. However, only a small subset of those would have to be memorized - those which are relevant to the individual. I'd agree that this particular pattern doesn't have enough variability for each pattern to be unique enough to reliably identify it, but I'd conjecture that its possible to make such a pattern, which has enough variability and unique characteristics to be recognizable (ignoring the fact that an adversary could make a very similar pattern to mislead the individual - I'm not curious about it for verification.)

Your example of the fact that we can't reliably recognize every face on this planet is very interesting. Let's imagine we know n faces which I can reliably distinguish from one another, but now there is a (n+1)th face which I mix up with one of the previous ones. Now lets assume this face would instead have a very unique characteristic, unlike all previous faces - lets imagine for example, the nose on this face is upside down. Surely I'd be able to differentiate it from the previous n faces, hence the issue of identifying it might've been the limited variability/characteristics in the various previous instantiations of a face.

So there are a number of characteristics in a face, which have a certain degree of variability, which enable us to distinguish from a number of them. I've been pondering on how many of those characteristics could be combined in an object, and how high the variability could be; to create uniquely identifiable patterns. It probably depends a lot on the meaning we attribute to the pattern, different associations we have to it.

I apologize - quite the tangent, I guess. I've just been pondering a lot on this for a project I've been working on for some time.

Re: Representing SHA-256 Hashes as Avatars

#35

Post by littlestymaar »

g_sch wrote: post #28
sva_ wrote: post #23

Earlier quoted context omitted.

> The space of possible avatars (2^256, in this case) is far, far larger than the number of distinct objects that humans can distinguish between. That sounds intriguing to me. Are you aware of any research into this?

It's a simple order of magnitude calculation. 2^256 is greater than one billion to the eighth power, times 100,000. There are probably several possible ways you could estimate how many different objects a person could distinguish between, but I think it's unlikely you'd come up with even a single billion.

> but I think it's unlikely you'd come up with even a single billion.

One billion is really really tiny though, let's just play a game :

- Unless you're colorblind, you can easily tell ten hues apart. Let's pick two colors, one with a saturated hue, and the other with a pastel one. That's 100 possibilities.

- I'm pretty sure you can easily recognize pictures of a hundred people you've met at some point in your life. Let's pick two of them, that's 10 thousand combinations.

- can you recognize ten different road signs? Ten country shapes ? Ten animals ? Ten fictional character? Ten books cover? Ten celebrities? Just pick three categories, and you've got a thousand combinations.

Now I'm pretty sure you can tell your grandma sitting under a vivid pink UK shape next to your 9th grade math teacher staring at Bruce Willis holding a giant light blue stop sign apart from any other imaginable combinations.

An untrained[1] human brain probably cannot distinguish between 2^256 items, but it's still able to do it for massive numbers.

[1]: but maybe it's possible with training: for instance, chess professionals might be able to do it.

Re: Representing SHA-256 Hashes as Avatars

#38

Post by thehappypm »

franky47 wrote: post #7
kop316 wrote: post #4

As a warning, this would not be good for colorblind people (such as myself). The "Hello, Hacker News!" Hash's middle ring has half it's ring that looks identical to me, and unless I looked carefully, that entire ring looked the same to me.

What would you suggest as a solution ? I considered swapping Hue for Lightness in order to increase contrast changes. Would you be interested in testing out some variants ?

I am also colorblind. The gold standard is to use a color palette that is engineered for color blindness, which uses a suite of color-blind-friendly colors and heavily utilizes lightness. Here's a good article on an example from Tableau: https://public.tableau.com/en-us/s/blog/2013/10/choosing-col...

Re: Representing SHA-256 Hashes as Avatars

#39

Post by [deleted] »

nemo1618 wrote: post #24
sva_ wrote: post #23

Earlier quoted context omitted.

> The space of possible avatars (2^256, in this case) is far, far larger than the number of distinct objects that humans can distinguish between. That sounds intriguing to me. Are you aware of any research into this?

To be honest, I have no idea how many distinct objects humans can distinguish between, but I am 99% confident that it is fewer than 2^128, much less 2^256. I suppose it's a somewhat nuanced question, though. For example, if I were shown every avatar in sequence, I'm quite sure I would always notice the "diff" between two consecutive avatars. But the bar that I have in mind is much, much higher: given a sequence of av…

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