Design And Research Of The Combined Pseudo-random Number Generator

Pseudo-random number generator is widely used in the fields of computer simulation andinformation security; randomness, unpredictability, and generation rate of pseudo-randomnumber sequence is highly valuable to efficiency and safety of application system. This thesisdesigns a combined pseudo-random number sequence generation algorithm based on the superprime numbers, and by using FPGA hardware implementation and performance testing arecarried out.The thesis makes an in-depth study on and discussion in generation principle, existingmethods, and related statistical testing methods and standards of the pseudo-random sequence. Inthe proposed modular algorithm, firstly, random initial seed and the parameters are obtained bythe clock counter; then by making use of the special nature of the super prime numbers generatorare obtained “0” sequence and “1” sequence of the same probability; next through the disruptfunction “0” and “1” sequences are disrupted and reordered; at last, SHA₁secure hashalgorithm is used to further diverge the sequences in order to enhance the randomness of thesequence. This algorithm, with the introduction of uncertainty and high-speed conversion,obtains the irregular “0” and “1” sequences through the parity of the data and reduces thecorrelation between the generated data, and increases the cycle of pseudo-random sequence bytimely changing the related parameters of the generator.In order to assess the speed and statistical properties of the pseudo-random numbergenerator, the hardware implementation of the algorithm is completed in the FPGA by usingVerilog HDL; the experimental results show that the designed pseudo-random number generatorgenerates makes a good performance in randomness and can be applied in the field ofinformation security. Generated sequence pass all project inspection on FIPS140-2and NIST SP800-22international standard detection set. Experimental results show that the design of thepseudo-random number generator uses fewer resources and the generated sequences with goodrandomness having certain practical value.