Propose a new firefly-fast learning network model based intrusion-detection system

• Main Authors: Badran, Mohammed Falih, Moorthy, Kohbalan, Zukifi, Nor Saradatul Akmar, Mohamad, Mohd Saberi, Deris, Safaai, Md.Sahar, Nan
• Format: Article
• Published: Blue Eyes Intelligence Engineering & Sciences Publication 2019
• Subjects: T Technology (General); TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
• Online Access: http://eprints.uthm.edu.my/4730/; https://dx.doi.org/ 10.35940/ijitee.L1027.10812S219
• Institution: Universiti Tun Hussein Onn Malaysia

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 FA-FLN based on the Firefly algorithm and Fast Learning Network.