A new hybrid teaching learning based optimization -extreme learning machine model based intrusion-detection system

• Main Authors: Alsudani, Mustafa Qahtan, Abbdal Reflish, Salah, Moorthy, Kohbalan, Adnan, Myasar Mundher
• Format: Article
• Language: English; English
• Published: Elsevier Ltd 2023
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/40450/1/A%20new%20hybrid%20teaching%20learning%20based%20optimization%20-extreme.pdf; http://umpir.ump.edu.my/id/eprint/40450/2/A%20new%20hybrid%20teaching%20learning%20based%20optimization%20-extreme%20learning%20machine%20model%20based%20intrusion-detection%20system_ABS.pdf; http://umpir.ump.edu.my/id/eprint/40450/; https://doi.org/10.1016/j.matpr.2021.07.015; https://doi.org/10.1016/j.matpr.2021.07.015

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.