Genetic Algorithm with elitism for cryptanalysis of Vigenere cipher

In today's world, with increasing usage of computer networks and internet, the importance of network, computer and information security is obvious. One of the widely used approaches for information security is Cryptography. Cryptanalysis is a way to break the cipher text without having the encryption key. This paper describes a method of deciphering encrypted messages of Vigenere cipher cryptosystems by Genetic Algorithm using elitism with a novel fitness function. Roulette wheel method, two point crossover and cross mutation is used for selection and for the generation of the new population. We conclude that the proposed algorithm can reduce the time complexity and gives better results for such optimization problems.