2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 21 , Issue 1 , PP: 79-88, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Dunia Alawi Jarwan 1 , Omar Fitian Rashid 2 * , M. Jasim Mohammed 3 , Shaymaa E. Sarhan 4 , Hind Moutaz Al-Dabbas 5 , Maythem K. Abbas 6
Doi: https://doi.org/10.54216/FPA.210106
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.
Features Selection , Intrusion Detection , Misuse , RNA encoding , Matching algorithm
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