Network intrusion detection system by using genetic algorithm

• Main Authors: Harun, A.F (Author), Mohamad, R. (Author), Musirin, I. (Author), Suhaimi, H. (Author), Suliman, S.I (Author)
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2019
• Subjects: Genetic algorithm; Intrusion detection; Pattern recognition
• Online Access: View Fulltext in Publisher; View in Scopus

 Developing a better intrusion detection systems (IDS) has attracted many researchers in the area of computer network for the past decades. In this paper, Genetic Algorithm (GA) is proposed as a tool that capable to identify harmful type of connections in a computer network. Different features of connection data such as duration and types of connection in network were analyzed to generate a set of classification rule. For this project, standard benchmark dataset known as KDD Cup 99 was investigated and utilized to study the effectiveness of the proposed method on this problem domain. The rules comprise of eight variables that were simulated during the training process to detect any malicious connection that can lead to a network intrusion. With good performance in detecting bad connections, this method can be applied in intrusion detection system to identify attack thus improving the security features of a computer network. Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved.