Cellular-Genetic Key Generation Algorithm

The Genetic Algorithm (GA) requires randomized initial population so as to give requisite results. The work proposes the use of Cellular Automata (CA) to generate the initial population for GA. The numbers generated by clubbing these two processes will make a better set of random numbers as compared to existing methodologies. The quality of the random numbers generated has been tested by Gap Test and Karl Pearson coefficient of correlation test. So as to ensure the goodness of random numbers coefficient of auto correlation has also been calculated. This technique can be used to generate keys in cryptography and it will be nearly impossible to guess the key as both the techniques are of natural ethos and not mathematical in nature. Keywords— Random Number Generator, Cellular Automata, Genetic Algorithms, Cryptography, Vernam Cipher.