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

• 主要な著者: Badran, Mohammed Falih, Moorthy, Kohbalan, Zukifi, Nor Saradatul Akmar, Mohamad, Mohd Saberi, Deris, Safaai, Md.Sahar, Nan
• フォーマット: 論文
• 言語: English
• 出版事項: Blue Eyes Intelligence Engineering & Sciences Publication 2019
• 主題: TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
• オンライン･アクセス: http://eprints.uthm.edu.my/704/1/DNJ9727_7d7fc08ded10dafb3d6ff412d15ccc31.pdf; http://eprints.uthm.edu.my/704/; https://doi.org/10.35940/ijitee.L1027.10812S219

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.