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Thread: New "Jitter Entropy" RNG Proposed For Linux

  1. #1
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    Default New "Jitter Entropy" RNG Proposed For Linux

    Phoronix: New "Jitter Entropy" RNG Proposed For Linux

    The Linux kernel RNG implementation for providing random numbers has worked quite well for its years in use. However, a new jitter entropy generator implementation has been proposed that is capable of providing 100 kB/s throughput of randomness...

    http://www.phoronix.com/vr.php?view=MTI5NzY

  2. #2
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    Default Hardware RNG

    Doesn't all new CPUs come with a built-in hardware (P)RNG?

  3. #3
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    Quote Originally Posted by uid313 View Post
    Doesn't all new CPUs come with a built-in hardware (P)RNG?
    A PRNG doesn't actually provide entropy.

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    Quote Originally Posted by uid313 View Post
    Doesn't all new CPUs come with a built-in hardware (P)RNG?
    http://en.wikipedia.org/wiki/RdRand (uses RNG to seed PRNG)
    http://en.wikipedia.org/wiki/Hardwar...or#Clock_drift (VIA C3)

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    Quote Originally Posted by Ex-Cyber View Post
    A PRNG doesn't actually provide entropy.
    Are you sure?

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    Quote Originally Posted by Ex-Cyber View Post
    A PRNG doesn't actually provide entropy.
    For someone less technically inclined. What does this mean? What is entropy in this context and how does it differ from what a PRNG does? How does the proposed solution fix/handle that? Isn't what is being proposed here a PRNG, just a different one?

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    More entropy the better when you really want Random numbers.

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    Entropy is something that is unpredictable, hard to guess.
    PRNGs are algorithms that need to be seeded (keyed) with some entropy before they can output anything. Simple example of PRNG: http://en.wikipedia.org/wiki/RC4
    (T)RNGs get entropy from physical properties, like thermal noise, nuclear decay or in this case CPU timing jitter.
    (T)RNG is usually used to seed PRNG.
    Both types output statistical random data.

  9. #9
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    Quote Originally Posted by LightBit View Post
    Entropy is something that is unpredictable, hard to guess.
    PRNGs are algorithms that need to be seeded (keyed) with some entropy before they can output anything. Simple example of PRNG: http://en.wikipedia.org/wiki/RC4
    (T)RNGs get entropy from physical properties, like thermal noise, nuclear decay or in this case CPU timing jitter.
    (T)RNG is usually used to seed PRNG.
    Both types output statistical random data.
    I was under the impression that true random number generators couldn't be implemented in software due to computers being 100% deterministic, was I wrong?

  10. #10
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    Quote Originally Posted by Kristian Joensen View Post
    I was under the impression that true random number generators couldn't be implemented in software due to computers being 100% deterministic, was I wrong?
    No, you are not wrong. This proposal collects entropy from hardware.

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