Linux /dev/random - a new approach
The code in this repository provides a different approach to /dev/random which is called Linux Random Number Generator (LRNG) to collect entropy within the Linux kernel. The main improvements compared to the legacy /dev/random is to provide sufficient entropy during boot time as well as in virtual environments and when using SSDs. A secondary design goal is to limit the impact of the entropy collection on massive parallel systems and also allow the use accelerated cryptographic primitives. Also, all steps of the entropic data processing are testable.
The design and implementation is driven by a set of goals described in  that the LRNG completely implements. Furthermore,  includes a comparison with RNG design suggestions such as SP800-90B, SP800-90C, and AIS20/31.
The LRNG provides a complete separation of the noise source maintenance and the collection of entropy into an entropy pool from the post-processing using a pseudo-random number generator. Different PRNGs are supported, including:
Built-in ChaCha20 PRNG which has no dependency to other kernel frameworks.
SP800-90A DRBG using the kernel crypto API including its accelerated raw cipher implementations.
Arbitrary PRNGs registered with the kernel crypto API
Booting the patch with the kernel command line option "dyndbg=file drivers/char/lrng* +p" generates logs indicating the operation of the LRNG. Each log is prepended with "lrng:".
The LRNG has a flexible design by allowing an easy replacement of the deterministic random number generator component.
Implementation verification as well as performance tests are provided in the
The ChaCha20 DRNG used by the LRNG is implemented following standard pseudo- random number generator architectures. To analyze the characteristics of the ChaCha20 DRNG, the ChaCha20 DRNG is copied into a user space library which is available at .
The ChaCha20 DRNG code used for the LRNG is identical to the code in  which allows to apply conclusions drawn from  to be applied to the LRNG.
 ChaCha20 DRNG
Stephan Mueller firstname.lastname@example.org