Tongxin xuebao (Oct 2016)
Method for generating pseudo random numbers based on cellular neural network
Abstract
To overcome the degradation characteristics of chaos system due to finite precision effect and improve the sta-tistical performance of the random number,a new method based on 6th-order cellular neural network (CNN) was given to construct a 64-bit pseudo random number generation (PRNG).In the method,the input and output data in every iteration of 6th-order CNN were controlled to improved the performance of the random number affected by chaos degradation.Then the data were XORed with a variable parameter and the random sequences generated by a Logistic map,by which the repeat of generated sequences was avoided,and the period of output sequences and the key space were expended.Be-sides,the new method was easy to be realized in the software and could generate 64 bit random numbers every time,thus has a high generating efficiency.Test results show that the generated random numbers can pass the statistical test suite NIST SP800-22 completely and thus has good randomness.The method can be applied in secure communication and other fields of information security.