The role of the enhanced non-deterministic random number generator is to make conditioned entropy samples directly available to software for use as seeds to other software-based DRBGs. Values coming out of the ENRNG have multiplicative brute-force prediction resistance, which means that samples can be concatenated and the brute-force prediction resistance will scale with them. When two 64-bit samples are concatenated together, the resulting 128-bit value will have 128 bits of brute-force prediction resistance (264 * 264 = 2128). This operation can be repeated indefinitely and can be used to easily produce random seeds of arbitrary size. Because of this property, these values can be used to seed a DRBG of any size.
Insight 2006 scaricare key generator 32 bits Italiano
As described in section 3.2.3, the DRNG uses a deterministic random bit generator, or DRBG, to "spread" a conditioned entropy sample into a large set of random values, thus increasing the number of random numbers available by the hardware module. The DRBG autonomously decides when it needs to be reseeded, behaving in a way that is unpredictable and transparent to the RDRAND caller. There is an upper bound of 511 samples per seed in the implementation where samples are 128 bits in size and can provide two 64-bit random numbers each. In practice, the DRBG is reseeded frequently, and it is generally the case that reseeding occurs long before the maximum number of samples can be requested by RDRAND. 2ff7e9595c
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