A Design Of Combined Pseudo-random Number Generator

Random number generator is the "source" of information security and the "base" of cryptographic system.Since the birth of the network,there have been a variety of security problems,with the development of artificial intelligence,big data,cloud computing,Internet of things technology,people need to deal with more and more information security problems in the future.At present,the primary method to solve the problem of information security is to use various cryptographic technologies,and the essence of data protection by cryptographic technology is to "randomize" the data.In general,the results of randomization and the degree of randomization depend on the randomness of the key,initial vector,salt value and other information used by the cryptographic algorithm,which is initially generated by the random number generator in the cryptographic system.Therefore,the design of efficient and secure random number generator is very important for cryptography or security system.Cryptographic random number generator is divided into true random number generator and pseudo random number generator.True random number generator can only be realized by using expensive hardware,and it has disadvantages such as high demand for randomness of entropy source and slow speed of random number generation,so it is not practical and commercial.Pseudo-random number generator has many construction methods,such as based on block cipher,sequence cipher,Hash function and other cryptographic primitives,these construction methods are complex,and there are low efficiency.However,the combination-based pseudo-random number generator has the advantages of simple construction methods and obvious improvement on the statistical characteristics of the existing pseudo-random number generator.In this paper,a pseudo-random number generator algorithm is constructed based on the combination method.The specific research contents are as follows:(1)In this dissertation,a safe and efficient combined pseudo-random number generator algorithm is designed,which takes LCG algorithm and RC4 algorithm as the data generation source and the secure cryptographic Hash function as the data post-processing algorithm.The algorithm uses the full-period LCG algorithm with the module of 256 to make the "1" and "0" in the generating sequence uniformly distributed.(2)A counter is set inside the combined pseudo-random number generator,which is updated with random values in the process of each round of iteration,so that the value of the counter has a certain randomness.Since the internal state of the RC4 algorithm is taken as part of the internal state of the random number generator,the period of the new RC4 algorithm will be further increased when the Hash value of the internal counter is used to update or permutate the internal state of the RC4 algorithm.(3)XOR operation of the Hash values of the sequences generated by LCG algorithm and those generated by RC4 algorithm can enhance the anti-cryptographic analysis ability of the algorithm.Before the algorithm outputs random numbers,the internal state of the algorithm is processed by using the secure cryptography Hash function algorithm,which can effectively cut off the correlation between the generated random sequence and the internal state of the algorithm,so that the generated random sequence has unpredictability.(4)This dissertation not only analyzes the security of the scheme from an unpredictable perspective,but also designs a special test program and makes six specific test schemes.The test program is executed on different computer platforms according to the parameter specified by the six schemes.By recording,comparing and analyzing different test results,the performance of the combined pseudo-random number generator under different conditions can be known and evaluated.In order to further validate the statistical properties of the sequence generated by this pseudo random number generator,we use the widespread adoption of NIST SP800-22 randomness test kit to perform a sequence of statistical test.The test results show that the sequences generated by random number generator has good statistical properties,and can be applied to cryptography and information security filed,etc.