Desing and FPGA-based implementation of an efficient pseudo-random number generator (PRNG) with chaotic systems

Abstract

This thesis explores the design and FPGA implementation of a chaos-based pseudo-random number generator (PRNG) for cryptographic applications. Focusing on the Tinkerbell map, we analyze the effects of finite-precision arithmetic on chaotic systems and propose a novel perturbation mechanism (PPM) to mitigate dynamical degradation. The implemented PRNG demonstrates enhanced statistical randomness, extended cycle lengths, and hardware efficiency, validated through NIST tests and FPGA prototyping. Our results show that chaos-based PRNGs can provide secure, efficient alternatives to conventional methods in cryptography.