E-ISSN 3026-930X
 
2025, Vol: 3, Issue: 1
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Original Research 


Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment

Elizabeth Ozioma Edward, Joseph A Ojeniyi, Noah Ndakotsu Gana, Joseph Yisa Ndagi, Isah Tajiri Sagagi.


Abstract
The rapid growth of interconnected devices gives rise to potential exploits and compromise of devices in the Internet of Things environment, this therefore requires an effective checkmate. This study focuses on the detection of threat in an IoTs environment based on ensemble model. In the proposed ensemble model, an outlier analysis was performed to optimize the features in order to enhanced the proposed model’s performance, while Support Vector Machine and Feed Forward Neural Network served as the base learners which were combined using stacking technique to form the proposed ensemble model, to enhance the performance strength in the detection of intrusion threat in IoTs environment. The advantage of the proposed model is its ability to generate an enhanced performance evaluation output; as the result proves an excellent performance for intrusion detection in an Internet of Things environment. The obtained accuracy, precision, F-score, and recall of the proposed ensemble model are 99.96% respectively, and 3.42% False Alarm Rate, thus, outperforming the existing technique. This is a clear distinction of the superiority of the ensemble (Feed Forward Neural Network and Support Vector Machine) model, the proposed ensemble model can serve as a technique in mitigating intrusion threat experienced in IoTs environment.

Key words: SVM, FFNN, Ensemble, IoTs, Accuracy, Recall


 
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How to Cite this Article
Pubmed Style

Edward EO, Ojeniyi JA, Gana NN, Ndagi JY, Sagagi IT. Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. NJEAS. 2025; 3(1): 59-67. doi:10.5455/NJEAS.274856

Web Style

Edward EO, Ojeniyi JA, Gana NN, Ndagi JY, Sagagi IT. Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. https://www.nilejeas.com/?mno=274856 [Access: December 30, 2025]. doi:10.5455/NJEAS.274856

AMA (American Medical Association) Style

Edward EO, Ojeniyi JA, Gana NN, Ndagi JY, Sagagi IT. Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. NJEAS. 2025; 3(1): 59-67. doi:10.5455/NJEAS.274856


Vancouver/ICMJE Style

Edward EO, Ojeniyi JA, Gana NN, Ndagi JY, Sagagi IT. Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. NJEAS. (2025), [cited December 30, 2025]; 3(1): 59-67. doi:10.5455/NJEAS.274856


Harvard Style

Edward, E. O., Ojeniyi, . J. A., Gana, . N. N., Ndagi, . J. Y. & Sagagi, . I. T. (2025) Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. NJEAS, 3 (1), 59-67. doi:10.5455/NJEAS.274856


Turabian Style

Edward, Elizabeth Ozioma, Joseph A Ojeniyi, Noah Ndakotsu Gana, Joseph Yisa Ndagi, and Isah Tajiri Sagagi. 2025. Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. Nile Journal of Engineering and Applied Science, 3 (1), 59-67. doi:10.5455/NJEAS.274856


Chicago Style

Edward, Elizabeth Ozioma, Joseph A Ojeniyi, Noah Ndakotsu Gana, Joseph Yisa Ndagi, and Isah Tajiri Sagagi. "Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment." Nile Journal of Engineering and Applied Science 3 (2025), 59-67. doi:10.5455/NJEAS.274856


MLA (The Modern Language Association) Style

Edward, Elizabeth Ozioma, Joseph A Ojeniyi, Noah Ndakotsu Gana, Joseph Yisa Ndagi, and Isah Tajiri Sagagi. "Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment." Nile Journal of Engineering and Applied Science 3.1 (2025), 59-67. Print. doi:10.5455/NJEAS.274856


APA (American Psychological Association) Style

Edward, E. O., Ojeniyi, . J. A., Gana, . N. N., Ndagi, . J. Y. & Sagagi, . I. T. (2025) Ensemble Technique Based Model for Intrusion Detection in Internet of Things Environment. Nile Journal of Engineering and Applied Science, 3 (1), 59-67. doi:10.5455/NJEAS.274856


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1. Prof. Abdulhameed Danjuma Mambo
   Editor-in-Chief
abdulhameed.mambo@nileuniversity.edu.ng
2. Dr. Adekunle Adeleke
    Associate Editor-in-Chief
    adekunle.adeleke@nileuniversity.edu.ng
3. Dr. Ifeyinwa Obianyo
Managing Editor
ifeyinwa.obianyo@nileuniversity.edu.ng