Research And Design Of Pseudo Random Number Generator Based On Memristive Hyperchaotic System

In recent years,the rapid development of digital technology and the Internet has brought great convenience to people's work and life.At the same time,a large number of incidents such as information tampering and data leakage have occurred.Therefore,information security has increasingly become a real issue of concern to people.At present,in terms of information security,encryption is arguably the most direct and effective method,and random numbers are widely used in the field of information encryption.With the gradual improvement of chaos theory,close integration with other disciplines,and chaos's sensitivity to initial conditions,long-term unpredictability and ergodic characteristics,the application of chaos theory in the field of information security has become a popular research direction.Compared with chaotic systems,hyperchaotic systems have two or more positive Lyapunov exponents,with more complex dynamic characteristics,and thus attract more attention from researchers.In order to design chaotic(hyperchaotic)systems with more complex dynamic characteristics,scholars have brought memristors into chaotic systems,and the generated chaotic signals have more complex dynamic characteristics,which has become a new research hotspot in chaotic systems.Therefore,combining memristive hyperchaotic systems with random number generators is a very meaningful research topic.The research content of this article is as follows:1.A pseudo-random number generator with five-dimensional four-wing memristive hyperchaotic system as a single entropy source is proposed,and MATLAB software is used for simulation.Since the hyperchaotic system is a continuous-time chaotic system,when the random number generator is simulated,the hyperchaotic system must first be discretized,and then the generated hyperchaotic sequence is sampled and quantized.In order to make the distribution of the generated random sequence more uniform,a simple post-processing is performed on the quantized sequence.The post-processing method is composed of 16 shift registers and a 15-level XOR.Finally,the NIST 800.22 test and security analysis were performed on the random numbers generated after the simulation.The test and analysis results verify that the generated random number has good randomness,and also prove that this random number generator has potential application value in the field of information security.2.A pseudo-random number generator with an unbalanced four-wing memristor hyperchaotic system and Bernoulli mapping as a dual entropy source is proposed,and FPGA is used for hardware implementation.The FPGA implementation flow of the random number generator is mainly composed of 4 modules,which are entropy source,sampling,quantization(comparator)and post-processing.In the entropy source module,since the hyperchaotic system is a continuous-time chaotic system,it needs to be discretized first using the RK4 algorithm,and another entropy source Bernoulli map itself is a discrete-time chaotic system,which is not needed.In order to increase the speed of random sequence generation,in the quantization module,the sequence generated by the chaotic oscillator is pre-processed.Finally,NIST 800.22,ENT and AIS.31 tests and security analysis were performed on the random number generated by the random number generator.The results proved that the generated random number had good randomness.In addition,comparing the pseudo-random number generator with the random number generator in other literatures,the pseudo-random number generator has a faster output speed,which can reach 62.5Mbit/s.