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Well, I'm referencing a "random" number generated in someone's head, not one generated by a CSPRNG. But with regard to CSPRNGs, an implementation can have a fla

Well, I'm referencing a "random" number generated in someone's head, not one generated by a CSPRNG. But with regard to CSPRNGs, an implementation can have a flaw, and we have seen these sorts of things happen, a well known example is MD5, a hash function, which are similar in principle to PRNGs, was broken. My last paragraph basically amounts to if any of the axioms used for constructing any crypto are false then all cryptography based on them is breakable and this is not specific to any implementation. If they're not false, proper implementation works, and implementation details are more important. In principle, just using a provably random TRNG to generate a seed and then using a properly implemented CSPRNG to generate numbers from the seed, as long as the seed is provably destroyed the numbers are indistinguishable from random numbers. This is not true of "randomness" generated by the human brain. "You'd rather not bet on that being true" is exactly right, theoretically a human could produce a truly random number, but the likelihood is very low that no predictable external influence went into that process compared to using noise generated by the chaotic universe.

SilasX 5y ago
>Well, I'm referencing a "random" number generated in someone's head, not one generated by a CSPRNG. What is that responding to? I thought I made the distinction between which one I was addressing pretty clear. >But with regard to CSPRNGs, an implementation can have a flaw, and we have seen these sorts of things happen, a well known example is MD5, a hash function, which are similar in principle to PRNGs, was broken. True, but my point was that the algorithm can itself be flawed, even if implemented correctly. The point being, yes, you have Knightian uncertainty about the real factors that cause human-generated random numbers ... but you also have Knightian uncertainty about the existence of undiscovered flaws in your algorithm. Yes, you're much less likely to run into the flaw if you're using a CSPRNG based on a high-entropy source, but in both cases it's true, or at least, impossible to rule out, that "there are biases in it, you just don't know there are." Edit: And, FWIW, there aren't usable cryptosystems based on P=NP, which would actually be an improvement! Most are based on the far stronger assumption that certain "NP-intermediate" problems aren't feasibly solveable.

SilasX 5y ago

>Well, I'm referencing a "random" number generated in someone's head, not one generated by a CSPRNG. What is that responding to? I thought I made the distinction between which one I was addressing pretty clear. >But with regard to CSPRNGs, an implementation can have a flaw, and we have seen these sorts of things happen, a well known example is MD5, a hash function, which are similar in principle to PRNGs, was broken. True, but my point was that the algorithm can itself be flawed, even if implemented correctly. The point being, yes, you have Knightian uncertainty about the real factors that cause human-generated random numbers ... but you also have Knightian uncertainty about the existence of undiscovered flaws in your algorithm. Yes, you're much less likely to run into the flaw if you're using a CSPRNG based on a high-entropy source, but in both cases it's true, or at least, impossible to rule out, that "there are biases in it, you just don't know there are." Edit: And, FWIW, there aren't usable cryptosystems based on P=NP, which would actually be an improvement! Most are based on the far stronger assumption that certain "NP-intermediate" problems aren't feasibly solveable.