
Looking for Entropy in All the Wrong Places - signa11
https://nullprogram.com/blog/2019/04/30/
======
rwmj
We recently had this problem with nbdkit. Our server tries to be reasonably
portable across several platforms, and needs non-cryptographically secure
random numbers for various purposes including testing and error injection. I
ended up replacing all calls to rand() with two of the xoshiro generators.
These are actually faster than rand() with nicer properties.

[https://github.com/libguestfs/nbdkit/blob/master/common/incl...](https://github.com/libguestfs/nbdkit/blob/master/common/include/random.h)
[http://xoshiro.di.unimi.it/](http://xoshiro.di.unimi.it/)

Edit: Having read the full article now, he seems to jump between requiring
random numbers for monte carlo testing, and true entropy for cryptographic
purposes. These requirements seem at odds with each other, so perhaps better
to define the use case properly first.

------
0-_-0
Shouldn't Monte Carlo integration be done with low discrepancy sequences
instead of random numbers? See for example:
[https://i.imgur.com/cDMuP5p.jpg](https://i.imgur.com/cDMuP5p.jpg)

