Propose a new Firefly-Fast Learning Network model based Intrusion-Detection System

• Main Authors: Mohammed Falih, Badran, Kohbalan, Moorthy, Nor Saradatul Akmar, Zulkifli, Mohd Saberi, Mohamad, Safaai, Deris, Nan, Md. Sahar
• Format: Article
• Language: English
• Published: Blue Eyes Intelligence Engineering & Sciences Publication 2019
• Subjects: Q Science (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/28158/1/Journal%20Paper.pdf; http://umpir.ump.edu.my/id/eprint/28158/; http://www.ijitee.org/wp-content/uploads/papers/v8i12S2/L102710812S219.pdf
• Institution: Universiti Malaysia Pahang

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.