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Wyatt Heplerf9fb90f2020-09-30 18:59:33 -07001.. _module-pw_random:
Armando Montanez47008e82020-08-04 11:04:45 -07002
3---------
4pw_random
5---------
6Pigweed's ``pw_random`` module provides a generic interface for random number
7generators, as well as some practical embedded-friendly implementations. While
8this module does not provide drivers for hardware random number generators, it
9acts as a user-friendly layer that can be used to abstract away such hardware.
10
11Embedded systems have the propensity to be more deterministic than your typical
12PC. Sometimes this is a good thing. Other times, it's valuable to have some
13random numbers that aren't predictable. In security contexts or areas where
14things must be marked with a unique ID, this is especially important. Depending
15on the project, true hardware random number generation peripherals may or may
16not be available. Even if RNG hardware is present, it might not always be active
17or accessible. ``pw_random`` provides libraries that make these situations
18easier to manage.
19
20Using RandomGenerator
21=====================
22There's two sides to a RandomGenerator; the input, and the output. The outputs
23are relatively straightforward; ``GetInt()`` randomizes the passed integer
24reference, and ``Get()`` dumps random values into a the passed span. The inputs
25are in the form of the ``InjectEntropy*()`` functions. These functions are used
26to "seed" the random generator. In some implementations, this can simply be
27resetting the seed of a PRNG, while in others it might directly populate a
28limited buffer of random data. In all cases, entropy injection is used to
29improve the randomness of calls to ``Get*()``.
30
31It might not be easy to find sources of entropy in a system, but in general a
32few bits of noise from ADCs or other highly variable inputs can be accumulated
33in a RandomGenerator over time to improve randomness. Such an approach might
34not be sufficient for security, but it could help for less strict uses.
35
36Algorithms
37==========
38xorshift*
39---------
40The ``xorshift*`` algorithm is a pseudo-random number generation algorithm. It's
41very simple in principle; the state is represented as an integer that, with each
42generation, performs exclusive OR operations on different left/right bit shifts
43of itself. The "*" refers to a final multiplication that is applied to the
44output value.
45
46Pigweed's implementation augments this with an ability to inject entropy to
47reseed the generator throughout its lifetime. When entropy is injected, the
48results of the generator are no longer completely deterministic based on the
49original seed.
50
51Note that this generator is NOT cryptographically secure.
52
53For more information, see:
54
55 * https://en.wikipedia.org/wiki/Xorshift
56 * https://www.jstatsoft.org/article/view/v008i14
57 * http://vigna.di.unimi.it/ftp/papers/xorshift.pdf
58
59Future Work
60===========
61A simple "entropy pool" implementation could buffer incoming entropy later use
62instead of requiring an application to directly poll the hardware RNG peripheral
63when the random data is needed. This would let a device collect entropy when
64idling, improving the latency of potentially performance-sensitive areas where
65random numbers are needed.