Comparison of genetic algorithm optimization on artificial neural network and support vector machine in intrusion detection system

Abstract

As the technology trend in the recent years uses the systems with network bases, it is crucial to detect them from threats. In this study, the following methods are applied for detecting the network attacks: support vector machine (SVM) classifier, artificial Neural Networks (ANN), and Genetic Algorithms (GA). The objective of this study is to compare the outcomes of GA with SVM and GA with ANN and then comparing the outcomes of GA with SVM and GA with ANN and other algorithms. Knowledge Discovery and Data Mining (KDD CPU99) data set has been used in this paper for obtaining the results.