Evolutionary Operators-Based Particle Swarm Optimization (EOPSO) to Attack Classical Cryptography Methods

Abstract

Particle Swarm Optimization (PSO) is a population-based optimization tool, which could be implemented and applied easily to solve various function optimization problems and some NP-complete problems. This paper present a benefit developed PSO using two evolutionary operators: crossover and mutation, so it called Evolutionary Operators-based PSO (EOPSO). The benefit of these two operators in PSO is use as momentum and diversity tool in the population. EOPSO used to attack the two types of classical cryptography (substitution and transposition). Experimental results of EOPSO appear that the amount of recovered key of classical ciphers and fitness function values are best than with PSO, improved 2-opt PSO and simulated annealing PSO.