Multi-Type Pseudo-Random Numbers Generation Control and Transmission Based on Multistable Attractors With FPGA Implementation

Pseudo-random numbers generator (PRNG), as the core foundation of modern information science, has irreplaceable strategic value in the fields of cryptography and communication security. This paper proposes pseudo-random numbers (PRNs) generation and control algorithms based on the multistable mechanism. It aims to overcome the limitations of traditional PRNs in complexity and diversity. Specifically, a novel memristive Hopfield neural network (MHNN) is proposed, which can generate stereoscopic multi-scroll, homogeneous and heterogeneous attractors. Based on attractors with diverse characteristics, the scheme for generating PRNs is developed by using method of region division and initial condition control. To meet the adaptive needs of various application scenarios, the multi-steady-state control allocation strategy is designed, which includes steady-state timing switching mechanism. Finally, the PRNG is implemented based on field programmable gate array (FPGA). Then PRNs transmission test is carried out, and collected PRNs pass the randomness test. The above research aims to provide high-security, real-time solutions for secure communication.