Random number generation is a process in which a sequence of numbers or symbols that cannot be predicted better than by random chance is generated. The outcome sequence will contain some patterns that are impossible to see in hindsight. Hardware random-number generators (HRNGs) can be true random number generators, since each generation is a function of the current value of a physical environment’s attribute that is almost impossible to model. Random number generations done by pseudorandom number generators can be reproduced by knowing the state of the PRNG, unlike this. Various applications of randomness have led to the development of different methods for generating random data Rolling of dice, coin flipping, the shuffling of playing cards, and the use of yarrow stalks for divination are just some of the techniques that have been around for a long time. The mechanical nature of these techniques required a lot of time and work. Random number tables would be used to collect and distribute results. There are several methods for pseudorandom number generation. All fall short of the goal of true randomness, although they may meet with varying success, some of the statistical tests for randomness intended to measure how unpredictable their results are. They are generally not usable for applications such as cryptography. Special features designed for use in cryptography are included in the carefully designed.