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Hamizan Suhaimi
Universiti Teknologi MARA

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Genetic algorithm for intrusion detection system in computer network Hamizan Suhaimi; Saiful Izwan Suliman; Afdallyna Fathiyah Harun; Roslina Mohamad; Yuslinda Wati Mohamad Yusof; Murizah Kassim c
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1670-1676

Abstract

Internet connection nowadays has become one of the essential requirements to execute our daily activities effectively. Among the major applications of wide Internet connections is local area network (LAN) which connects all internet-enabled devices in a small-scale area such as office building, computer lab etc. This connection will allow legit user to access the resources of the network anywhere as long as authorization is acquired. However, this might be seen as opportunities for some people to illegally access the network. Hence, the occurrence of network hacking and privacy breach. Therefore, it is very vital for a computer network administrator to install a very protective and effective method to detect any network intrusion and, secondly to protect the network from illegal access that can compromise the security of the resources in the network. These resources include sensitive and confidential information that could jeopardise someone’s life or sovereignty of a country if manipulated by wrong hands.  In network intrusion detection system (NIDS) framework, apart from detecting unauthorized access, it is equally important to recognize the type of intrusions in order for the necessary precautions and preventive measures to take place. This paper presents the application of genetic algorithm (GA) and its steps in performing intrusion detection process. Standard benchmark dataset known as KDD’99 cup was utilized with forty-one distinctive features representing the identity of network connections. Results presented demonstrate the effectiveness of the proposed method and warrant good research focus as it promises exciting discovery in solving similar-patent of problems.   
Network intrusion detection system by using genetic algorithm Hamizan Suhaimi; Saiful Izwan Suliman; Ismail Musirin; Afdallyna Fathiyah Harun; Roslina Mohamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1593-1599

Abstract

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.
Network intrusion detection system using immune-genetic algorithm (IGA) Hamizan Suhaimi; Saiful Izwan Suliman; Ismail Musirin; Afdallyna Harun; Roslina Mohamad; Murizah Kassim; Shahrani Shahbudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1059-1065

Abstract

Network security is an important aspect in maintaining computer network systems and personal information from being illegally accessed by third parties. The major problem that frequently occurs in computer network systems is the failure in detecting possible network-attacks. Apart from that, the process of recognizing the type of attack that occurs is very crucial as it will determine the elimination process that should take place to counter the intrusion. This paper proposes the application of standard Genetic Algorithm (GA) that combines with immune algorithm process to enhance the computer system’s capability in recognizing possible intrusion occurrence in a computer system. Simulation was conducted numerous times to test the effectiveness of the proposed intrusion detection system by manipulating the parameter values for genetic operators utilized in GA. The effectiveness of the proposed method is shown in the gathered results and the analysis conducted further supports and proves that Immune Genetic Algorithm (IGA) has the capability to predict the occurrence of intrusion in computer network.
Co-Authors Afdallyna Fathiyah Harun Afdallyna Harun Ismail Musirin Murizah Kassim Murizah Kassim c Roslina Mohamad Saiful Izwan Suliman Shahrani Shahbudin Yuslinda Wati Mohamad Yusof