Method for generating pseudo random numbers based on cellular neural network

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,...

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Bibliographic Details
Main Authors: Li-hua DONG, Guo-li YAO
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2016-10-01
Series:Tongxin xuebao
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Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016252/
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Summary: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.
ISSN:1000-436X