Random Numbers : -

• Random numbers are useful for a variety of purposes, such as generating data encryption keys, simulating and modeling complex phenomena and for selecting random samples from larger data sets.

• They have also been used aesthetically, for example in literature and music, and are of course ever popular for games and gambling. When discussing single numbers, a random number is one that is drawn from a set of possible values, each of which is equally probable, i.e., a uniform distribution. When discussing a sequence of random numbers, each number drawn must be statistically independent of the others.

Various methods for random numbers generation : -

1. Pseudo-random number generator (PRNG) - Pseudo-random number generator uses algorithms to produce random results, often from short randomization seeds. Their generators are capable of high throughputs, but attackers can derive the random number from knowledge of the seed.

2. Hardware/true random number generator (TRNG) - Hardware/true random number generator measures a physical phenomenon expected to be random. Even though it can deliver high quality random, the rate is usually limited, resulting in entropy starvation that will impact performance, security, or both.

3. Hybrid random number generator - Hybrid random number generator uses both hardware and software derived randomness depending on the read rate needed and has similar qualities to the PRNG at high throughputs.

4. Quantum random number generators (QRNG) - Quantum random number generators measure true random directly from a quantum effect. It delivers full entropy and can do so at very high throughput. No seed is needed. QuintessenceLabs QRNG, qStream, delivers 100% entropy at 1 Gbit/s.