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RNG stands for random number generator, a device or algorithm that produces a sequence of numbers or symbols that cannot be reasonably predicted. Learn about the methods, applications and types of RNG, such as true and pseudorandom numbers.
These approaches combine a pseudo-random number generator (often in the form of a block or stream cipher) with an external source of randomness (e.g., mouse movements, delay between keyboard presses etc.). /dev/random – Unix-like systems; CryptGenRandom – Microsoft Windows; Fortuna
Random.org is a website that produces random numbers based on atmospheric noise. It offers free and paid tools to generate random sequences, simulate events, and act as a third-party arbiter for raffles and promotions.
A hardware random number generator (HRNG) is a device that generates random numbers from a physical process capable of producing entropy. Learn about the history, uses, and types of HRNGs, and how they differ from pseudorandom number generators (PRNGs).
Lavarand, also known as the Wall of Entropy, was a device that used lava lamps to produce random data for seeding a pseudorandom number generator. It was developed by Silicon Graphics and later used by Cloudflare for securing Internet traffic.
If one has a pseudo-random number generator whose output is "sufficiently difficult" to predict, one can generate true random numbers to use as the initial value (i.e., the seed), and then use the pseudo-random number generator to produce numbers for use in cryptographic applications.
A random number is generated by a random process such as throwing dice. Learn about the common understanding, real world consequences, and flaws of random number generation, as well as algorithms and implementations.
Learn how to test the randomness of a set of data or a number generator using various statistical tests, transforms, and complexity measures. See the list of common and widely used random number generators and their performance on different tests.