Statistical testing of random number generators and their improvement using randomness extraction

arXiv:2403.18716v1 Announce Type: new
Abstract: Random number generators (RNGs) are notoriously hard to build and test, especially in a cryptographic setting. Although one cannot conclusively determine the quality of an RNG by testing the statistical properties of its output alone, running numerical tests is both a powerful verification tool and the only universally applicable method. In this work, we present and make available a comprehensive statistical testing environment (STE) that is based on existing statistical test suites. The STE can …

arxiv build cryptographic cs.cr extraction hard improvement quality quant-ph random randomness running test testing tests verification