Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/3922 2018 2018 Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq Omar Omar Department of Geology, College of Science, University of Baghdad, Baghdad, Iraq Omar Fitian Rashid Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq M. Jasim Mohammed Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq Shaymaa E. Sarhan Department of Computer Science, College of Education for Pure Science/Ibn Al-Haitham, University of Baghdad, Baghdad, Iraq Hind Moutaz Al Al-Dabbas Asia Pacific University of Technology and Innovation Technology Park Malaysia, Bukit Jalil, 57000 Kuala Lumpur, Malaysia Maythem K. Abbas The significance of the Intrusion Detection System (IDS) is due to its capability in detecting attacks over the network. The current paper proposes a new feature selection method for misuse intrusion detection systems based on RNA encoding, where the proposed method includes five steps. Firstly, the KDD-Cup99 dataset is used and then select random records are used for both training and testing. Secondly, RNA encoding to encode each possible value in the dataset into RNA characters. Thirdly, the keys and their locations are extracted by dividing the achieved RNA sequences from previous steps into blocks with different sizes, then finding the most repeated blocks, choosing them as keys, and storing their location. The next step is the proposed feature selection method based on the extracted keys and their locations, depending on the place of the key within the feature number. Finally, the Raita algorithm for matching to search for keys before and after the applied features selection method. In terms of IDS performance evaluation, experimental outcomes of the proposed feature selection method show the capability of optimizing the time complexity and metrics.   2026 2026 79 88 10.54216/FPA.210106 https://www.americaspg.com/articleinfo/3/show/3922