Ideal quantum random number generators (QRNGs) can produce algorithmically and thus incomputable sequences, in contrast to pseudo-random generators. However, the verification of presence algorithmic randomness incomputability is a nontrivial task. We present results search for output from two different QRNGs, performed by applying tests based on Solovay-Strassen test primality Chaitin-Schwartz ...

Computers are deterministic devices and a computer-generated random number is a contradiction in terms. As a result, computer-generated pseudorandom numbers are fraught with peril for the unwary. We summarize much that is known about the most well-known pseudorandom number generators: congruential generators. We also provide machine-independent programs to implement the generators in any langua...

The paper presents a simple true random number generator (TRNG) which can be embedded in digital Application Specific Integrated Circuits (ASICs) and Field Programmable Logic Devices (FPLDs). As a source of randomness, it uses on-chip noise generated in the internal analog phaselocked loop (PLL) circuitry. In contrast with traditionally used free running oscillators, it uses a novel method of r...

The paper presents a simple true random number generator (TRNG) which can be embedded in digital Application Specific Integrated Circuits (ASICs) and Field Programmable Logic Devices (FPLDs). As a source of randomness, it uses on-chip noise generated in the internal analog phaselocked loop (PLL) circuitry. In contrast with traditionally used free running oscillators, it uses a novel method of r...

Random and pseudorandom number generators (RNG and PRNG) are used for many purposes including cryptographic, modeling and simulation applications. For such applications a generated bit sequence should mimic true random, i.e., by definition, such a sequence could be interpreted as the result of the flips of a fair coin with sides that are labeled 0 and 1. It is known that the Shannon entropy of ...

The generation of uniform pseudo-random numbers between 0 and 1 is important in many numerical simulations. The purpose of this report is to explore the best generator(s) of such random numbers in terms of statistical properties and speed. While attempting to find the best generator in general, the specific goal of this report is to find the best generator for Latin hypercube sampling [Iman and...

With the rapid development and wide use of Internet, information transmission faces a big challenge of security. People need a safe and secured way to transmit information. Encryption is a common method, which is used for encrypting information. But it is easier to attract the attention of the attackers because the information cannot be read directly. The information will be intercepted, deciph...

An incremental pseudorandom bit generator (iPRBG) is backtracking resistant if a state compromise does not allow the attacker a non-negligible advantage at distinguishing previouslygenerated bits from uniformly distributed random bits. Backtracking resistance can provide increased security in cryptographic protocols with long-term secrecy requirements. While a necessary condition for an iPRBG t...

The paper presents a new statistical bias in the distribution of the first two output bytes of the RC4 keystream generator. The number of outputs required to reliably distinguish RC4 outputs from random strings using this bias is only 2 bytes. Most importantly, the bias does not disappear even if the initial 256 bytes are dropped. This paper also proposes a new pseudorandom bit generator, named...