Developing a Hybrid Pseudo-Random Numbers Generator

Pseudo-random numbers (PRNs) play a vital role in many fields, such as cyber security, simulations, games, and statistical analysis. They provide the level of unpredictability necessary for secure communication and data protection. A Pseudo Random Number Generator (PRNG) is an important tool that can generate number sequences exhibiting statistical properties similar to that of True Random Numbers (TRNs). This paper proposes a PRNG based on multiple principles: feature extraction, biometrics, and a 6D hyperchaotic system. The proposed tool combines these three topics in a specific order to utilize the randomization inherent in each one. The resulting sequence (LPB-chao sequence) underwent a set of randomization tests to ensure its randomization. These tests were applied inside the proposed tool to produce only randomly strong sequences and reject the weak ones. The practical experiments proved that there is great key sensitivity, and the execution time is linearly proportional to the length of the generated sequence.