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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. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.
Random seed. A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator . For a seed to be used in a pseudorandom number generator, it does not need to be random. Because of the nature of number generating algorithms, so long as the original seed is ignored, the rest of the values that ...
The XOR cipher is often used in computer malware to make reverse engineering more difficult. If the key is random and is at least as long as the message, the XOR cipher is much more secure than when there is key repetition within a message. When the keystream is generated by a pseudo-random number generator, the result is a stream cipher.
Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers). RNG is a gaming term that refers to the generation of random numbers.
A nonce is an arbitrary number used only once in a cryptographic communication, in the spirit of a nonce word. They are often random or pseudo-random numbers. Many nonces also include a timestamp to ensure exact timeliness, though this requires clock synchronisation between organisations. The addition of a client nonce (" cnonce ") helps to ...
For the formal concept in theoretical computer science, see Pseudorandom generator. A pseudorandom number generator ( PRNG ), also known as a deterministic random bit generator ( DRBG ), [1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...
A pseudorandom sequence of numbers is one that appears to be statistically random, despite having been produced by a completely deterministic and repeatable process. [1] Simply put, the problem is that many of the sources of randomness available to humans (such as rolling dice) rely on physical processes not readily available to computer programs.