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

页码：2701 / 2705

页数：4

共 50 条

[31] HYBRID MACHINE LEARNING TECHNIQUE FOR INTRUSION DETECTION SYSTEM
Tahir, Hatim Mohamad
Hasan, Wael
Said, Abas Md
Zakaria, Nur Haryani
Katuk, Norliza
Kabir, Nur Farzana
Omar, Mohd Hasbullah
Ghazali, Osman
Yahya, Noor Izzah
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON COMPUTING & INFORMATICS, 2015, : 464 - 472
[32] Improved Ant Colony Optimization and Machine Learning Based Ensemble Intrusion Detection Model
Vanitha, S.
Balasubramanie, P.
INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2023, 36 (01): : 849 - 864
[33] Blockchain Assisted Fireworks Optimization with Machine Learning based Intrusion Detection System (IDS)
Thiruvenkatasamy, Sudhakar
Sivaraj, Rajappan
Vijayakumar, Murugasamy
TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2024, 31 (02): : 596 - 603
[34] A hybrid machine learning model for intrusion detection in VANET
Hind Bangui
Mouzhi Ge
Barbora Buhnova
Computing, 2022, 104 : 503 - 531
[35] Hybrid intrusion detection system using machine learning
Meryem A.
Ouahidi B.E.
Network Security, 2020, 2020 (05) : 8 - 19
[36] Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection
Maseno, Elijah M.
Wang, Zenghui
JOURNAL OF BIG DATA, 2024, 11 (01)
[37] Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection
Elijah M. Maseno
Zenghui Wang
Journal of Big Data, 11
[38] MACHINE LEARNING-BASED ANDROID INTRUSION DETECTION SYSTEM
Tahreem, Madiha
Andleeb, Ifrah
Hussain, Bilal Zahid
Hameed, Arsalan
arXiv,
[39] Intrusion Detection System Based on Machine Learning Algorithms: A Review
Amanoul, Sandy Victor
Abdulazeez, Adnan Mohsin
2022 IEEE 18TH INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING & APPLICATIONS (CSPA 2022), 2022, : 79 - 84
[40] Intrusion Detection System for AI Box Based on Machine Learning
Chen, Jiann-Liang
Chen, Zheng-Zhun
Chang, Youg-Sheng
Li, Ching-Iang
Kao, Tien-I
Lin, Yu-Ting
Xiao, Yu-Yi
Qiu, Jian-Fu
2023 25TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY, ICACT, 2023, : 111 - 116

← 1 2 3 4 5 →