CRFeb 24, 2017
Yet Another Pseudorandom Number Generator
arXiv:1702.07502v113 citations
Originality Synthesis-oriented
AI Analysis
This addresses data security for cryptographic applications, but appears incremental as it combines existing components.
The authors tackled the problem of generating pseudorandom numbers by proposing a new scheme based on the Rössler attractor and bent Boolean function, resulting in a high level of data security as shown by cryptanalysis and statistical tests.
We propose a novel pseudorandom number generator based on Rössler attractor and bent Boolean function. We estimated the output bits properties by number of statistical tests. The results of the cryptanalysis show that the new pseudorandom number generation scheme provides a high level of data security.