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In computing, entropy is the randomness collected by an operating system or application for use in cryptography or other uses that require random data. This randomness is often collected from hardware sources (variance in fan noise or HDD), either pre-existing ones such as mouse movements or specially provided randomness generators.
In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), [1] or physical random number generator[2][3] is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a physical ...
Here S is the entropy of the system; T k is the temperature at which the heat enters the system at heat flow rate ˙; ˙ = ˙ = ˙ represents the entropy flow into the system at position k, due to matter flowing into the system (˙, ˙ are the molar flow rate and mass flow rate and S mk and s k are the molar entropy (i.e. entropy per unit ...
Lavarand. Lavarand, also known as the Wall of Entropy, was a hardware random number generator designed by Silicon Graphics that worked by taking pictures of the patterns made by the floating material in lava lamps, extracting random data from the pictures, and using the result to seed a pseudorandom number generator. [1]
RDRAND (for "read random") is an instruction for returning random numbers from an Intel on-chip hardware random number generator which has been seeded by an on-chip entropy source. [ 1 ] It is also known as Intel Secure Key Technology, [ 2 ] codenamed Bull Mountain. [ 3 ] Intel introduced the feature around 2012, and AMD added support for the ...
When read, the /dev/random device will only return random bytes within the estimated number of bits of noise in the entropy pool. When the entropy pool is empty, reads from /dev/random will block until additional environmental noise is gathered. [7] The intent is to serve as a cryptographically secure pseudorandom number generator, delivering ...
There are several "pools" of entropy; each entropy source distributes its alleged entropy evenly over the pools; and (here is the key idea) on the nth reseeding of the generator, pool k is used only if n is a multiple of 2 k. Thus, the kth pool is used only 1/2 k of the time. Higher-numbered pools, in other words, (1) contribute to reseedings ...
A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weak entropy source, together with a short, uniformly random seed, generates a highly random output that appears independent from the source and uniformly distributed. [1] Examples of weakly random sources include radioactive decay or ...