Cryptanalysis of DES Using Computational Intelligence
Cryptanalysis of block cipher is a challenging task due to non-linearity in nature. Recently Cryptanalysis using Computational Intelligence pave the way to break the block ciphers. In this paper, by combining the effectiveness of Genetic Algorithm and Particle Swarm Optimization, a novel approach, called Genetic Swarm Optimization is proposed and applied in the field of cryptanalysis for attacking DES. A known plaintext attack is used and varieties of optimum keys are computed. Through this approach, the optimum key can be found faster without searching the entire key space. The experimental result indicates that Genetic Swarm Optimization can be used in the field of cryptanalysis efficaciously in order to break the key and also can be applied to attack other block ciphers.