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Would a "bad" random number seed (like reading values from ADC) negatively affect the security of SRP6a? Yes. At least, a reused random on the server side enables replay of a captured session. On the client side, I think (without detailed analysis) that a predictable RNG can be used to extract secret information allowing login, or even the ...


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So, what's wrong with a p-value close to 1? Because random sequences don't look 'perfectly random' (or, rather, they have a low probability of doing so). We're checking if this sequence quacks [1] like a perfectly random sequence; acting 'too uniform' is evidence that it is not. [1]: from the proverb "if it acts like a duck, and it quacks like a duck,...


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Why such naive and simple thing is not appealing If you're talking about a method that internally generates 500,000 0 bits and 500,000 1 bits, shuffles them (by some method), and then outputs them, that would not be considered a CSRNG. What is the "real" compass? The compass is "can we devise an efficient test that distinguishes the output ...


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tl;dr– It's not actually a true-random generator so much as a physically-sourced-random generator. The underlying physical processes can have patterns that compression helps to strip away, improving the quality of the generator. In context, "true" randomness is referring to randomness sourced from physical phenomena in contrast to pseudo-...


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I see this as being relatively straight forward. If the compression algorithm could detect the next chunk of data from the previous chunks of data such that it was able to reliably compress it. Then it wasn't a great random chunk anyway, so there's not much benefit in including all of it in your 'secure' coding. If you compress it, then it can still ...


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I think you're misinterpreting the source. The source says the TRNGs "rely" on compression (a cryptographic hash would be the compression function, or possibly some simpler function to increase throughput). The random data isn't insecure after compression, it's insecure before compression. Why? When you roll dice there's an equal probability of it ...


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First, that's not the Next Bit Test, which is purely theoretical, but rather an attempt at a practical approximation of it. From your first citation: The notation $O(\nu(n))$ is used for any function, $f(n)$, that vanishes faster than the inverse of any polynomial, that is for every polynomial, $poly(n)$, and $n$ large enough, $f (n) < 1/poly (n)$. So you ...


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But this notation is defined (informally) in the first paper. The notation $O(\nu(n))$ is used for any function, $f(n)$, that vanishes faster than the inverse of any polynomial, that is for every polynomial, $\mathrm{poly} (n)$, and $n$ large enough, $f(n) \leq 1/\mathrm{poly}(n)$ Therefore, what it means is no probabilistic polynomial time (PPT) algorithm ...


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