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Board Development & Technical Discussion
Merits 1 from 1 user
Re: How can you verify the randomness that's coming from a hardware?
by
goldkingcoiner
on 02/05/2022, 22:10:59 UTC
⭐ Merited by vapourminer (1)
Unfortunately even with entropy as low as in the super-cooled superconductors of quantum computers you would still hit the wall for physical measurements that we call Heisenberg's Uncertainty Principle.

You can generate the randomness artificially with mathematics and code alone, yes. Low entropy would be technically impossible to detect if you ignore the physics perspective and don't create your randomness generator with only a few lines of code and a limited output or input.
Or fortunately that quantum computers have this as a problem, leaving security for all of banking!

I think there are a few different questions here:
1) What is random enough to provide security for generational wealth?
2) What is the most random system that you could ever create?
3) Are there sources that we think are random that could ever be backtraced or controlled?
4) Even if you have a purely random source, how do you ensure a flat spectral density?

It doesn't take much to make something be impossibly random.
I recommend a very different style of book, "A Short Stay in Hell", which deals with a man who has to overcome randomness to get out of hell.

Interesting questions indeed. I will try a stab at them but I am sure everyone else in the Development & Technical Discussion subforum knows a lot more about it than me. So take my answers with a grain of salt.

1. I think you can make anything infinitely random but that all means nothing if someone reads your code to understand how the randomness is generated. So your randomness is only as good as your security.
2. decentralised data from as many high entropy sources for the input and a multitude of security layers?
3. lets take a look for example at weather. Even with current technology we cannot accurately predict the weather. Nobody technically knows if tomorrow will be 0.1 degrees hotter or colder than predicted. Although that is a not so good example due to how limited our temperature can be.
4. Not sure. Perhaps by adding white noise by descrete time sequences?