Abstract: To mitigate the safety issue caused by the loss of precision of the state value of the floating-point number during the iteration, an integer piecewise Logistic map is proposed by integer processing. The proposed method redefines the multiplication operation of the integer utilizing the uniformity of transient data in the finite precision, which makes the output state values of the model having more uniform distribution probability density and ensure its security. Furthermore, a pseudo-random number generator algorithm is proposed. The proposed algorithm combines the one-dimensional cellular automata with the S-box substitution mechanism, which reduces the coupling between state values and improves the complexity of the algorithm. Performance analysis and simulation experimental results show that the integer chaotic map used in the scheme has uniform probability density distribution and complex dynamic behavior, and the pseudo-random sequences generated by the proposed scheme has high complexity, strong security, and good efficiency. Therefore, the proposed scheme has good application prospects in the field of data security.

Key words: integer chaos system, piecewise Logistic map, pseudorandom number generator, data security