Evaluation of the Efficiency of Advanced Number Generators in Cryptographic Systems using a Comparative Approach

This study explores the effectiveness and security impact of two pseudorandom number generators (PRNGs): the Fibonacci Random Number Generator (FRNG) and the Gaussian Random Number Generator (GRNG) in cryptographic systems. By applying statistical tests, the research aims to determine which of these generators provides a more robust level of randomness, thus boosting the security of cryptographic applications. The approach involves generating sequences of random integers using Java implementations of both FRNG and GRNG, followed by an analysis with the Chi-Square Test and Kolmogorov-Smirnov Test. Results show that the Gaussian PRNG produces numbers that align more consistently with a uniform distribution, while the Fibonacci PRNG shows notable irregularities. This points to the need for rigorous testing of RNGs to uphold security and reliability in cryptographic systems. The study’s outcomes carry important implications for choosing cryptographic algorithms, emphasizing the crucial role of high-quality RNGs in safeguarding data confidentiality, integrity, and authenticity.