How Random is Your RNG? | NIST

Benjamin Rainer, Jürgen Pilz, Martin Deutschmann

Leonardo Errati, Roberto La Scala, Mauro Patano

Random number generators (RNGs) are an often overlooked cornerstone for secure communications, cryptographic protocols, and scientific simulations. This workshop opens with an overview of the NIST framework for RNGs - from entropy sources to filters and test suites. An important conclusion is that the construction of secure, standardised Quantum RNGs is a multidisciplinary effort; this will be exemplified by an ongoing integration project for distributed IT infrastructures

John Gaebler, Adam M. Meier, Ting Rei Tan +8 more

João Dionísio, Tiago Mota, Iola Pinto +1 more

We present a random number generator (RNG) testing application in LabVIEW®, based on six of the statistical tests from the ubiquitous NIST test suite that is widely used in the field of cryptography. The implementation is described, and tests measuring performance, both regarding precision and speed, are demonstrated. The application can be interfaced to real time true RNGs based on quantum optics experiments.

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.

Hoang Minh Ngo, Etienne-Alexandre Scraire, Miguel Angel Mora