Intrusion-detection system based on hybrid models: review paper
The Intrusion-detection systems (IDS) is currently one of the most important security tools. However, an IDS-based hybrid model offers better results than crime detection using the same algorithm. However, hybrid models based on conventional algorithms still face different problems. The objective of...
Main Authors: | , , , |
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Format: | Conference or Workshop Item |
Language: | English |
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2020
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Online Access: | http://eprints.uthm.edu.my/6218/1/P12453_811c4422b426a632d0060d86f804cc01.pdf |
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author | Badran, Mohammed Falih Md. Sahar, Nan Sari, Suhaila Taujuddin, N. S. A. M. |
author_facet | Badran, Mohammed Falih Md. Sahar, Nan Sari, Suhaila Taujuddin, N. S. A. M. |
author_sort | Badran, Mohammed Falih |
collection | UTHM |
description | The Intrusion-detection systems (IDS) is currently one of the most important security tools. However, an IDS-based hybrid model offers better results than crime detection using the same algorithm. However, hybrid models based on conventional algorithms still face different problems. The objective of this study was to provide information on the most important assumptions and limitations of close hybrid analysis based on criminal analysis and to analyze the limitations of the new machine learning algorithm (FLN) to obtain IDS-based advice. |
first_indexed | 2024-03-05T21:53:15Z |
format | Conference or Workshop Item |
id | uthm.eprints-6218 |
institution | Universiti Tun Hussein Onn Malaysia |
language | English |
last_indexed | 2024-03-05T21:53:15Z |
publishDate | 2020 |
record_format | dspace |
spelling | uthm.eprints-62182022-01-31T07:07:10Z http://eprints.uthm.edu.my/6218/ Intrusion-detection system based on hybrid models: review paper Badran, Mohammed Falih Md. Sahar, Nan Sari, Suhaila Taujuddin, N. S. A. M. TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) The Intrusion-detection systems (IDS) is currently one of the most important security tools. However, an IDS-based hybrid model offers better results than crime detection using the same algorithm. However, hybrid models based on conventional algorithms still face different problems. The objective of this study was to provide information on the most important assumptions and limitations of close hybrid analysis based on criminal analysis and to analyze the limitations of the new machine learning algorithm (FLN) to obtain IDS-based advice. 2020 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/6218/1/P12453_811c4422b426a632d0060d86f804cc01.pdf Badran, Mohammed Falih and Md. Sahar, Nan and Sari, Suhaila and Taujuddin, N. S. A. M. (2020) Intrusion-detection system based on hybrid models: review paper. In: International Conference on Technology, Engineering and Sciences (ICTES) 2020, 18 April 2020, Penang, Malaysia. https://doi.org/10.1088/1757-899X/917/1/012059 |
spellingShingle | TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) Badran, Mohammed Falih Md. Sahar, Nan Sari, Suhaila Taujuddin, N. S. A. M. Intrusion-detection system based on hybrid models: review paper |
title | Intrusion-detection system based on hybrid models: review paper |
title_full | Intrusion-detection system based on hybrid models: review paper |
title_fullStr | Intrusion-detection system based on hybrid models: review paper |
title_full_unstemmed | Intrusion-detection system based on hybrid models: review paper |
title_short | Intrusion-detection system based on hybrid models: review paper |
title_sort | intrusion detection system based on hybrid models review paper |
topic | TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) |
url | http://eprints.uthm.edu.my/6218/1/P12453_811c4422b426a632d0060d86f804cc01.pdf |
work_keys_str_mv | AT badranmohammedfalih intrusiondetectionsystembasedonhybridmodelsreviewpaper AT mdsaharnan intrusiondetectionsystembasedonhybridmodelsreviewpaper AT sarisuhaila intrusiondetectionsystembasedonhybridmodelsreviewpaper AT taujuddinnsam intrusiondetectionsystembasedonhybridmodelsreviewpaper |