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Eldho, Arya (2024) Advancing Network Intrusion Detection Systems through Machine Learning Algorithms. Masters thesis, Dublin, National College of Ireland.
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Abstract
Network intrusions pose a significant threat to cybersecurity. To secure the data being transferred online an Intrusion Detection System(IDS) is needed. IDSs detect intrusions in networks. In the study proposed here a machine learning based IDS is built. The machine learning models, SVM, Random Forest(RF), KNN, and the Convolutional Neural Network-Gated Recurrent Unit-Bidirectional Long Short Term Memory(CNN-GRU-BiLSTM) models are used in the study. The dataset used in the study is the NSLKDD dataset. The dimensionality of the features in the dataset is reduced using both Recursive Feature Elimination (RFE) and Principal Component Analysis(PCA). The data is balanced using Synthetic Minority Oversampling (SMOTE). These models were trained and evaluated to get the best model to detect the intrusions in NIDS. The results of the study show that the best performance is shown by the CNN-GRU-BiLSTM when it is used along with the RFE as it achieved a validation accuracy of 97%. The study also shows that the accuracy of a machine learning model increases if the dimensionality of its features is reduced. The CNN-GRU-BiLSTM is used to build a desktop application and the desktop application is able to successfully detect and classify intrusions. The IDS model is developed successfully. The machine learning models and the desktop application are built using Python.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Basilio, Jorge UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Data Analytics |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 15 Aug 2025 18:16 |
| Last Modified: | 15 Aug 2025 18:16 |
| URI: | https://norma.ncirl.ie/id/eprint/8559 |
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