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submitted 11 months ago by throws_lemy@lemmy.nz to c/physics@mander.xyz
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[-] FooBarrington@lemmy.world 3 points 11 months ago

I know what you're trying to get at, but my point is this: Imagine you have two streams of data, one from a CSPRNG, and one from what you call "true randomness". How can you tell which one is which (as long as you're staying under the CSPRNGs limit from your initial entropy)?

If you can't tell me a way, there is no functional difference between these two options. So what advantage would true randomness hold?

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

I said this in another comment, but while I agree that there is virtually no functional difference, and in the vast majority of cases truly random and functionally random are equivalent, that doesn’t mean that something which is functionally random is truly random.

[-] FooBarrington@lemmy.world 3 points 11 months ago

But it is truly random for all intents and purposes, since the input is truly random. Just because the process contains deterministic steps doesn't mean the input entropy isn't true entropy anymore.

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

And a pool is clean for all intents and purposes. There is still a distinction though. The fact that it is deterministic inherently makes it less random than true randomness.

[-] FooBarrington@lemmy.world 3 points 11 months ago

The input is not deterministic.

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

If you take the original values used to determine the final “random number” and run them through the same sequence of calculations, you will always reach the same value.

We rely on the fact that the inputs are so numerous and/or difficult to replicate to deem the final value “random”. But that doesn’t mean that the value cannot be reached by a second party given perfect knowledge of the original state of all inputs.

True randomness, on the other hand, is impossible to calculate even with that perfect knowledge, because we aren’t relying on the state of inputs running through a calculation.

[-] FooBarrington@lemmy.world 3 points 11 months ago* (last edited 11 months ago)

But that's my point: just because you apply deterministic steps to a truly random input doesn't make the output not truly random. You use real entropy as your starting point, which is literally exactly what you call "true randomness". This means the output has the same level of "true randomness" as your "truly random" input, because you mathematically don't lose entropy along the way.

To put it more simply: you're arguing from a philosophical perspective, not a mathematical one.

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

The input is not truly random though. If it was, we could just use that input, with no other steps, and have a truly random output. You’re confusing an unknown state with randomness.

[-] FooBarrington@lemmy.world 2 points 11 months ago

No, it actually and literally is truly random. You'd need to know everything about the hardware itself and the environment around it in incredible detail (incl. the temperature of every individual small patch of material, air flow and the state of air in and around the case) to reliably predict the initial entropy for a given modern system, since tiny changes in e.g. temperature will completely change the input.

It's only a small bit of entropy, but enough to kick-start the RNG in a way that can reliably create high-quality entropy.

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

So you’re literally arguing that knowable inputs, however unlikely knowing those inputs might be, run through known deterministic calculations, results in a guaranteed unknowable output?

[-] FooBarrington@lemmy.world 2 points 11 months ago

No, I'm arguing that the inputs aren't knowable to the required degree in the general case, which defines their entropy, and that entropy isn't mathematically lost, it's improved through deterministic calculations.

[-] KairuByte@lemmy.dbzer0.com 0 points 11 months ago

The same was thought about previous iterations on random number generators. The first I am aware of used an extremely precise time stamp, and ran the calculations on that. On the assumption that no one could possibly know the exact timestamp used. That was obviously untrue, which can be verified by the fact that such systems have been broken before.

Just because you can’t conceive of a way to know the values, does not make them unknowable. It just makes it improbable to happen.

And again, I’m not saying the random numbers we can produce now are currently breakable. But that doesn’t mean that a decade from now, or even a century, they will remain unbroken.

[-] FooBarrington@lemmy.world 2 points 11 months ago

Say I'm restarting my phone, and it uses details like temperature fluctuations in CPU sensors as entropy. How would you know all the required values? Since I'm holding the phone in my hand, the temperature of my hand (and consequently body temperature) are relevant, not to mention the air around my phone. How would you find those values at the exact time the sensors are read?

[-] KairuByte@lemmy.dbzer0.com 1 points 10 months ago

You honestly think those values aren’t possible to estimate within a range then brute force?

That’s like asking “say I hit a button at a very specific time, how would you find that exact time?”

[-] FooBarrington@lemmy.world 1 points 10 months ago

Yes, because 1) you'd need to know them with incredible precision, and 2) you can't brute force, because you only have one chance. Otherwise you can also brute force anything that's "truly random" as you put it.

That’s like asking “say I hit a button at a very specific time, how would you find that exact time?”

That's the thing, it's not like that. It's more like "say I hit a button at a very specific time and roll hundreds of dice, how would I find that exact time and all the results of those dice".

[-] KairuByte@lemmy.dbzer0.com 1 points 10 months ago

Apart from the face that there are absolutely no “dice rolls” involved. They are known deterministic calculations. Because in order to add “dice rolls” you would need randomness. You can’t have a non deterministic calculation involved, because that isn’t how computers work.

You’re essentially saying “take a knowable input, add true randomness, output true randomness using nothing but knowable inputs!”

And you absolutely can brute force it. Why would you have a single chance? Because of arbitrary rules?

As for true randomness, you’re getting a range of “extreme low to extreme high” which isn’t currently brute forcible.

[-] FooBarrington@lemmy.world 1 points 10 months ago* (last edited 10 months ago)

My dude, the "dice rolls" are all the small pieces of entropy that you'd have to know the environment to an unknowable degree for. They are conceptually absolutely involved, and if you can't understand that, we're done here, because you're handwaving over the difficult parts in a way that doesn't make sense.

[-] KairuByte@lemmy.dbzer0.com 1 points 10 months ago

Those “dice rolls” are not random though. The problem is you keep talking about these inputs as if they themselves are random. They aren’t. And just because you can’t fathom a way to know their values now, doesn’t mean they are unknowable. I point back to the timestamp issue, where at the time it was considered “enough” but was disproven as such years down the line.

this post was submitted on 26 Oct 2023
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