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If the goal is cryptographic strength [given the context stated by the OP, I assume it is] in a PRNG that will be used in practice, then the randomness testing methods can be used to rule out generators as being weak, but obviously cannot rigorously demonstrate randomness. However there are pitfalls in using generators which are based on problems which are ...


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It is worth mentioning that there is a connection in complexity theory often called "Hardness v Pseudorandomness" that makes this question somewhat difficult. It may not be surprising that given a strong enough PRG, one can derandomize certain randomized algorithms, i.e. trying to prove $P = BPP$ can be done by giving a provably strong enough ...


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You want a speed that's hard to reach even for a simple operation such as xoring the PRNG output with some data. You aren't going to get that speed for a CSPRNG except maybe with some serious dedicated hardware engineering. But you don't need this! Sequential speed is not relevant for a PRNG with unspecified hardware. If you need more PRNG speed than your ...


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It does, but it's practically impossible to evaluate how much: just a tiny little bit, or enough for security? A PC is an extremely complex thing, and it's practically impossible to know its exact state at a precise moment in time, even having observed its external behavior (user actions, network packets…) very precisely. Even knowing the exact state of the ...


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Or course it does. That's the foundational basis of /dev/random. I'm not going to repeat what's already well documented. Please read Documentation and Analysis of the Linux Random Number Generator. What's not really spelt out is where the entropy comes from. It comes from quantization noise. It's the attempt of digital systems to accurately model analogue ...


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The first thing to NOTE is that said by SEJPM in the comment, performance depends on the hardware - in both horizontal (core count, etc.) and vertical (clock speed, etc.) dimensions. The second thing to understand is that, although CSPRNGs and stream ciphers can share underlaying primitive, their security requirements are different. So now, let's get started ...


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No, not really. Your schematic is missing a crucial component called a decimator. The output of coupled ring oscillators (ROs) in the real world tends to not have as much jitter as in idealised literature. Essentially, there's little jitter as they tend to synch together under one system clock. It can look like:- The output from your NOR gates will be ...


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I'll assume the right 16 in the question's figure is to tell that the LFSR is unloaded 16 bits at a time; and unless otherwise stated I'll assume that's done every 16 clock cycles of the LFSR. Is the LFSR sufficient to unbias the input? Mostly yes, but that's not enough in crypto. It's desired to make the output undistinguishable from random (no just ...


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Please don't. TestU01 or NIST? Neither. Trust what they say on the xoshiro256+ website. A CSPRNG is not defined by it's speed. It's defined by security against predictability, i.e. the next bit test. And that's determined by it's construction. All that TestU01, NIST's STS and all the others do is check for uniform randomness of output (within a certain ...


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Use a Zenner diode as noise generator, take sample of the noise voltage on the diode (through a capacitor), amplify it and measure the voltage with a ADC. After this process, extract the square root of this value and keep only the mantisa (numeric part after decimal point). It should deliver absolute true random numbers.


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AFAICT, this framework injects entropy directly into the underlying cryptographic primitive instead of treating the entropy collection/estimation and randomness extraction as two separate phases. Is my understanding correct? Yes, that's my understanding as well. What quantitative benefits does this framework have over the more traditional seed-based design?...


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The paper's use of "seedless" is very confusing as they aren't getting rid of internal state ... which is a seed, just a slightly different one. At 85 pages, the paper is also just very long. The problem I see the paper appears to address (after skimming through the text for a while), include: the chicken and egg situation with seed and ...


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I will take a slightly different approach, a side step to a simpler problem to gain intuition. Let's say we have a fair 6 sided die. And we wish to draw a number uniformly from 1 to 4. It can't be done with a single dice roll. The single dice roll has enough entropy. More than the 2 bits we need. But it is impossible to map the dice roll results to a ...


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