How Does a Random Number Generator Work and What is its Usage?

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A random number generator (RNG) can be classified as either "true" or "pseudo." True random number generators (TRNGs) derive randomness from physical processes, such as radioactive decay or thermal noise, while pseudo random number generators (PRNGs) use mathematical algorithms to produce sequences that appear random. PRNGs require an initial value, known as a seed, which influences the output sequence. Cryptographically secure random number generators (CSPRNGs) are a type of PRNG designed to be secure against adversaries, ensuring their output is indistinguishable from true randomness. Understanding these distinctions is crucial for applications in fields like cryptography, gaming, and statistical sampling.
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How does a random number generator work ?
What is the usage of it ?
 
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phion said:
I don't want to use it right now,I need to know how does it work ? Is there different ways to arrive a number o there is only one way ? And where can we use random number generator ?
 
shahrzad1994 said:
I don't want to use it right now,I need to know how does it work ? Is there different ways to arrive a number o there is only one way ? And where can we use random number generator ?

A "true" random number generator (RNG or TRNG) works by measuring something physical which is theorized to behave randomly (such as radioactive decay) or something which is so complicated that it is sure to behave randomly (such as thermal noise). Any number of sources or measuring techniques can be used. Post-processing can be used to improve the quality of poor sources.

A "pseudo" random number generator (PRNG) works by having a computer perform a series of arithmetic or logical computation that results in what appears, at first glance, to be just a list of jumbled up numbers. This can be something as simple as a multiplicative-congruential generator, a linear feedback shift register or something more complicated. Typically a PRNG will have a "seed" -- an initial value that determines how the stream will start and an internal state that evolves as each pseudo-random number is emitted. The size of the internal state constrains how long it will take before the output stream begins to repeat itself.

A cryptographically secure random number generator (CSPRNG) is a pseudo random number generator which is good enough that an opponent with bounded computer power is unable to distinguish its output from a truly random stream. There are a variety of approaches that can be used. Multiplicative congruential and linear feedback shift registers are too easy to crack and are not cryptographically secure.
 
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