A new hybrid teaching learning based Optimization -Extreme learning Machine model based Intrusion-Detection system

被引：3
|
作者：
Qahatan Alsudani M. [1 ]
Abbdal Reflish S.H. [1 ]
Moorthy K. [2 ]
Mundher Adnan M. [3 ,4 ]
机构：
[1] Computer Techniques Engineering Department, Faculty of Information Technology, Imam Ja'afar Al-sadiq University, Najaf
[2] Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan
[3] Islamic University, Najaf
[4] Faculty of Engineering, School of Computing, Universiti Teknologi Malaysia, Johor Bahru
来源：
Mater. Today Proc. | 2023年 / 2701-2705期
关键词：
Fast Learning Network; Intrusion detection system; Optimization;
D O I：
10.1016/j.matpr.2021.07.015
中图分类号：
学科分类号：
摘要：
Currently, effective Intrusion-detection systems (IDS) still represent one of the important security tools. However, hybrid models based on the IDS achieve better results compared with intrusion detection based on a single algorithm. But even so, the hybrid models based on traditional algorithms still face different limitations. This work is focused on providing two main goals; firstly, analysis based on the main methods and limitations of the most-recent hybrid model-based on intrusion detection, secondly, to propose a novel hybrid IDS model called TLBO-ELM based on the Firefly algorithm and Fast Learning Network. © 2021
引用
收藏
页码：2701 / 2705
页数：4
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