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Random password generator. A random password generator is a software program or hardware device that takes input from a random or pseudo-random number generator and automatically generates a password. Random passwords can be generated manually, using simple sources of randomness such as dice or coins, or they can be generated using a computer.
However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.
Jenkins hash function. 32 or 64 bits. XOR/addition. Bernstein 's hash djb2 [2] 32 or 64 bits. shift/add or mult/add. or shift/add/xor or mult/xor. PJW hash / Elf Hash. 32 or 64 bits.
Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.
The RSA SecurID authentication mechanism consists of a "token"—either hardware (e.g. a key fob) or software (a soft token )—which is assigned to a computer user and which creates an authentication code at fixed intervals (usually 60 seconds) using a built-in clock and the card's factory-encoded almost random key (known as the "seed").
Luhn algorithm. The Luhn algorithm or Luhn formula, also known as the " modulus 10" or "mod 10" algorithm, named after its creator, IBM scientist Hans Peter Luhn, is a simple check digit formula used to validate a variety of identification numbers. It is described in U.S. Patent No. 2,950,048, granted on August 23, 1960.
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 ...
A high quality random number generation (RNG) process is almost always required for security, and lack of quality generally provides attack vulnerabilities and so leads to lack of security, even to complete compromise, in cryptographic systems. [1] The RNG process is particularly attractive to attackers because it is typically a single isolated ...