Maurer’s test is nowadays a basic statistical tool for testing physical random number generators in cryptographic applications. Based on a statistical analysis of this test we propose simple and effective methods for its improvement. These methods are related to the m spacing technique common in goodness-of-fit problems and the L leave out method used for a noise reduction in the final Maurer t...

Fast and reliable pseudo-random number generators are required for simulation and other applications in Scientific Computing. We outline the requirements for good uniform random number generators, and describe a class of generators having very fast vector/parallel implementations with excellent statistical properties. We also discuss the problem of initialising random number generators, and con...

An all-digital True Random Number Generator (TRNG) harvesting entropy from the collapse of 2 edges injected into one even-stage ring is fabricated in 40nm CMOS. A configurable ring and tuning loop provides robustness across a wide range of temperature (-40 to 120°C), voltage (0.6 to 0.9V), process variation, and external attack. The dynamic tuning loop automatically configures the ring to meet ...

For remote deployment of sensors in potentially hostile environments it is crucial to both ensure that the data is private and trust that the data originated from the sensor in question, at the alleged time and location of sensing, and without tampering. However, another critical requirement is to minimize energy consumption in computation and communication. We satisfy these often contradictory...

Random Number Generators play a critical role in a number of important applications. In practice, statistical testing is employed to gather evidence that a generator indeed produces numbers that appear to be random. In this paper, we reports on the studies that were conducted on the compressed data using 8 compression algorithms or compressors. The test results suggest that the output of compre...

Monte Carlo methods rely on sequences of random numbers to obtain solutions many problems in science and engineering. In this work, we evaluate the performance different pseudo-random number generators (PRNGs) Curand library a modern Nvidia GPU cards. As numerical test, generate (PRN) non-uniform distributions using acceptance-rejection method. We consider GPU, CPU, hybrid CPU/GPU implementatio...