aspg-3-3922-1791419272 20261008002752 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2026 21 1 Dunia Alawi Jarwan Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq Omar Fitian Rashid Department of Geology, College of Science, University of Baghdad, Baghdad, Iraq M. Jasim Mohammed Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq Shaymaa E. Sarhan Department of Mathematics, College of Science, University of Anbar, Ramadi, Iraq Hind Moutaz Al-Dabbas Department of Computer Science, College of Education for Pure Science/Ibn Al-Haitham, University of Baghdad, Baghdad, Iraq Maythem K. 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mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi; mso-ansi-language:TR;} 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 79 88 3922 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.210106 https://www.americaspg.com/journal/3/article/3922 https://www.americaspg.com/storage/21752858641.pdf