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

被引：2

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

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页码：2701 / 2705

页数：4

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