Building an Integrated IoT Security Framework for Smart Homes

Ravi, Sandra (2024) Building an Integrated IoT Security Framework for Smart Homes. Masters thesis, Dublin, National College of Ireland.

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Abstract

The analysis in this paper provides a new learning-based IDS that will support the security of smart homes with IoT technology. To execute the model, with the help of BoTNeTIoT_L01 and RT_IOT2022 datasets, the proposed approach presumed EDA where in it focuses its analysis on anomalies and imbalance of class labels of the target variable. To solve this problem, the application of SMOTE (Synthetic Minority Oversampling Technique) was implemented to balance the two classes hence allowing training to proceed fairly. I implemented six machine learning algorithms such as Decision Tree, Random Forest, Logistic Regression, LightGBM, XGBoost, and Multilayer Perceptron and used accuracy, precision, recall, F1 score, and ROC AUC to measure model performance. The best models were serialized using the joblib tool to fit into smart home systems to detect real-time intrusions. This pipeline provides an effective, expandable and realistic approach to developing solutions for emerging IoT security problems, translating research ideas and concepts into practice, while moving the state of the art of intrusion detection in smart homes forward.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Heffernan, Niall UNSPECIFIED
Uncontrolled Keywords:	Smart Homes; Machine learning; Real Time Application; Streamlit; Data Analysis
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 T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	28 Jul 2025 10:21
Last Modified:	28 Jul 2025 10:21
URI:	https://norma.ncirl.ie/id/eprint/8251

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