Method for generating pseudo-random numbers on basis of cellular neural networks

Abstract

The invention discloses a method for generating pseudo-random numbers on the basis of cellular neural networks. By the aid of the method, problems of low pseudo-random number generation efficiency and poor statistical performance in the prior art mainly can be solved. The implementation scheme includes that the method comprises 1), generating random sequences P by the aid of the six-dimensional cellular neural networks and generating random sequences X by the aid of logic mapping so as to enhance the randomness of the random sequences; 2), respectively storing the generated random sequences P and X into two different matrixes and carrying out integer processing on data of the matrixes so as to extract the randomness of decimal portions of the data; 3), acquiring a novel matrix from the two different processed matrixes and generating 64 bits of the pseudo-random numbers by the aid of data in the novel matrix in each procedure. The method has the advantages that the pseudo-random number generation efficiency can be improved; requirements of international random number detection standards NIST SP800-22 can be met by the generated pseudo-random numbers, and the generated pseudo-random numbers can be used for secure communication.

Description

Technical field [0001] The invention belongs to the field of information security, and particularly relates to a pseudo-random number generation method, which can be used for network information encryption. Background technique [0002] Random numbers can be seen everywhere in cryptographic applications, such as keys, digital signatures and identity authentication. There are two main types of common random number generation methods: true random number generator TRNG and pseudo random number generator PRNG. The true random number generator TRNG has good unpredictability. There have been many studies using noise as an external random source to construct the generator, such as Wu Xiaoyong and Wang Xinya's patents (patent publication number: CN103049243A) true random number generation method and device, Random numbers are generated by amplifying the quantization error in the analog-to-digital conversion and digital-to-analog conversion process, and then summing and amplifying the in...

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Problems solved by technology

[0004] The purpose of the present invention is to address the deficiencies in the prior art above, to propose a method for generating pseudo-random numbers based on cellular neural networks, to avoid the defects of low generation efficiency and insufficient statistical performance of random number generators, and to improve the security of information encryption sex

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