Network intrusion detection system by using genetic algorithm
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 con...
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Natura: | EJournal Article |
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Institute of Advanced Engineering and Science,
2019-12-01.
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LEADER | 02302 am a22003373u 4500 | ||
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001 | ijeecs20391_13196 | ||
042 | |a dc | ||
100 | 1 | 0 | |a Suhaimi, Hamizan |e author |
100 | 1 | 0 | |e contributor |
700 | 1 | 0 | |a Suliman, Saiful Izwan |e author |
700 | 1 | 0 | |a Musirin, Ismail |e author |
700 | 1 | 0 | |a Harun, Afdallyna Fathiyah |e author |
700 | 1 | 0 | |a Mohamad, Roslina |e author |
245 | 0 | 0 | |a Network intrusion detection system by using genetic algorithm |
260 | |b Institute of Advanced Engineering and Science, |c 2019-12-01. | ||
500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20391 | ||
520 | |a 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. | ||
540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
546 | |a eng | ||
690 | |||
690 | |a Intrusion detection, Genetic algorithm, Pattern recognition | ||
655 | 7 | |a info:eu-repo/semantics/article |2 local | |
655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
655 | 7 | |2 local | |
786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 16, No 3: December 2019; 1593-1599 | |
786 | 0 | |n 2502-4760 | |
786 | 0 | |n 2502-4752 | |
786 | 0 | |n 10.11591/ijeecs.v16.i3 | |
787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20391/13196 | |
856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20391/13196 |z Get fulltext |