The Intrusion Detection Using Random Forest Classifier: A Machine Learning Approach with Advanced Metrics

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ID: 312423
2026
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Abstract
To protect the network assets, online business, and user banking information from hacking or fraud. Advanced and multi layered security is needed to control these issues. In modern days, the use of artificial intelligence in our daily life activities is increasing day by day. Different type of machine learning algorithms that comes from AI help us to solve our problems. In this paper, the machine learning algorithm, random forest classifier, is proposed to improve the intrusion detection system. The WSN dataset used in this paper is multiclass. After the proposed model performance, a comparison is presented between different machine learning algorithms. The proposed model shows an accuracy of 0.995%, which shows the best results after comparison.
Reference Key
imported_1776990033_69eab75154cb6 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Humza Rana
Journal Southern Journal of Computer Science
Year 2026
DOI
DOI not found
URL
https://sjcs.isp.edu.pk/index.php/SJCS/article/view/14
Keywords Keywords not found

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