Effects of the random number generator on computer simulations

Werner Schindler

Frederic P. Miller, Agnes F. Vandome, John McBrewster

Hardware Random Number Generator. Computing, Cryptographically secure pseudorandom number generator, Random number generator attack, Random number generation, Applications of randomness, Randomness extractor, Johnson? Nyquist noise, Photoelectric effect

André Stefanov, Nicolas Gisin, Olivier Guinnard +2 more

A physical random number generator based on the intrinsic randomness of quantum mechanics is described. The random events are realized by the choice of single photons between the two outputs of a beamsplitter. We present a simple device, which minimizes the impact of the photon counters ’ noise, dead-time and after pulses. Random numbers are employed today as well for numerical simulations as for cryptography. Unfortunately computers are not able to generate true random numbers, as they are deterministic systems. Numerical pseudo-random generators rely on complexity [1]. Although such pseudo-random numbers can generally be employed for numerical computation, such as Monte-Carlo simulations, their use in cryptography, for example to generate keys, is more critical. The only way to get true random numbers, hence true security for crypto-systems, is to build a generator based on a random physical phenomenon [2,3,4]. As quantum theory is intrinsically random, a quantum process is an ideal base for a physical random number generator. The randomness of a sequence of numbers can be extensively tested, though not proven. It is thus of interest to thoroughly understand the behavior of the random process, so as to gain

C.H. Vincent

Safa Hanköylü

Randomness occurs in every kind of application in which random events should be experienced such as gambling, statistical calculations, computer simulations, information security and encryption. The quality of randomness is very important for the events using randomness. In particular, the need for random numbers used in the field of cryptology to be unpredictable increases the importance of random number generators. \n \nRandom Number Generators (RNGs) are software or hardware components that can be used to generate numbers that cannot be predicted in any pattern or relationship. Software-based RNGs are deterministic applications, while hardware-based RNGs are the devices that can be integrated into the system. \n \nEncryption using numbers generated by software-based RNG can be broken in varying times depending on the strength of the encryption because it was developed in deterministic ways. It is expected that the decoding time will be shortened considerably by the quantum computers which are tried to be developed today besides classic computers that takes a long time to analyze. The hardware RNGs are more powerful in randomness quality than software-based generators, but cost-effective and use-limited generators. \n \nQuantum Random Number Generators (QRNGs) is a kind of generator based on quantum physics laws instead of classical physics. In photonic based QRNGs are produced the random numbers after various software and hardware operations by taking advantage of the uncertainty of photons. These generated numbers are unpredictably strong random numbers. \n \nIn this study, a QRNG was obtained by using the RGB (Red-Green-Blue) values of the images taken from a white-single LED light source and the randomness tests of the produced numbers were carried out with the tests provided by NIST (National Institute of Standards and Technology). As a result, the numbers derived from the images successfully passed NIST tests and true random number sequences were obtained.

Roohi Zafar, Muhammad Kamran, Tahir Malik +4 more