Performance Evaluation of Selection Methods of Genetic Algorithm and Network Security Concerns

Abstract

Security is the prominent concern for the network and maintaining security is highly recommended. There exists several approaches has been attempted to address this challenging task. This paper presents the applicability of the genetic algorithm (GA) for security concerns. The working of the GA heavily depends on the various factors includes: reproduction operators, selection techniques, chromosome representation and problem type. There exist several selection methods presents play a vital role, but identifying the suitable one is a grand and persistent challenge. In this paper, a comparison of various selection techniques in the GA has been reported. The GA utilizes operators: crossover, mutation and selection to guide the searching in an iterative manner. A significant work has been conducted explains the importance of crossover and mutation probabilities, but very few researchers (some of them has shown the comparison of selection methods) presented the importance of selection approaches. The comparison of three: Rank based, Roulette wheel and Tournament selection techniques have been presented in this paper over Travelling Salesman Problem. Computational experiments have been conducted and results are collected considering distance should be as minimum as possible. Statistical tests (Paired T-Test and two ways ANOVA) are conducted to report the performance significance of selection techniques considered.