The implementer of an empirical test for random number generators is faced with some difficult problems, especially if the test is based on a statistic which is known only approximately: How can the test be tested? How can the approximation be improved? When is it good enough? A number of principles can be applied to these problems. These principles are illustrated using implementations of the ...

This paper presents an efficient filtering system for a metastable state-based true random number generator. To output a result with high randomness, we use loop-storage for storing the value of metastability. During the metastable state, the output value is accumulated to the storage. When the non-metastable state arises, the stored metastable value will be used for output instead of the resul...

This paper focuses on the design and implementation of a high-quality and high-throughput true-random number generator (TRNG) in FPGA. Various practical issues which we encountered are highlighted and the influence of the various parameters on the functioning of the TRNG are discussed. We also propose a few values for the parameters which use the minimum amount of the resources but still pass c...

Random mappings from a nite set into itself are either a heuristic or an exact model for a variety of applications in random number generation, computational number theory, cryptography, and the analysis of algorithms at large. This paper introduces a general framework in which the analysis of about twenty characteristic parameters of random mappings is carried out: These parameters are studied...

The use of a pseudo-random number generator to produce test cases for software appears not to be widely used, although the method has been reported in the literature for many years [1, 2, 4]. This paper draws on experience with this technique in two areas: compilers and software components. The use of a pseudo-random number generator to produce test cases which are expected to reflect actual us...

Randomness is of fundamental importance in various fields, such as cryptography, numerical simulations, or the gaming industry. Quantum physics, which is fundamentally probabilistic, is the best option for a physical random number generator. In this article, we will present the work carried out in various projects in the context of the development of a commercial and certified high speed random...

The meta-analysis of Intangible Brain-Machine Interaction (IMMI) data with random number generators (RNG’s) (Bösch, 2006) is re-evaluated through the application of rigorous and recognised mathematical tools. The current analysis shows that the statistical average of the true RNG-IMMI data is not shifted from chance by direct mental intervention, thus refuting the IMMI hypothesis. A facet of th...

In this letter, we present a circuit implementation for the discrete-time zigzag map, which exhibits high speed, low power consumption, and above all resilience to process variations. Circuit parameter variations result in alteration of the chaotic map parameters, such as the slope and the location of the breakpoints in the map, which in turn degrade the randomness of the generated bit sequence...

In this talk I will provide a description of recent uses Intel has made of cryptography in our platforms, including providing a hardware random number generator, using anonymous signatures, and improving performance of cryptographic algorithms. I will discuss how processor capabilities could be used more effectively by cryptographic algorithms. I will then discuss research questions in cryptogr...

To guarantee the security of uniform random numbers generated by a quantum random number generator, we study secure extraction of uniform random numbers when the environment of a given quantum state is controlled by the third party, the eavesdropper. Here we restrict our operations to incoherent strategies that are composed of the measurement on the computational basis and incoherent operations...