PRNG sequence combination techniques via Galois extension fields

The generation of pseudorandom number sequences can be achieved in a variety of ways, with the most secure methods generally requiring substantial processing to generate. Other pseudorandom number generation (PRNG) methods accept a compromise between processing power and security by mixing two independent, but less secure, PRNG outputs with each other. This paper presents a generalized mixing method for any number of PRNG streams using Galois Extension Field techniques that achieves maximal entropy when conditioned on any individual input, making the reverse engineering of the combined result exceedingly difficult. In addition to this basic mixing method, enhanced adaptations are presented that further improve the output while using simple bit-level statistical operators.