Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Feature Selection Study on the Bot-IoT Dataset Using Ensemble Classification Techniques Subject The topic of the resource Botnet attacks; Feature Selection; IoT Security; Machine Learning Description An account of the resource IoT is an emerging giant in the field of technol- ogy, taking over traditional systems, providing interconnected- ness, convenience, efficiency, and automation, making our lives unimaginably better. However, security for these IoT systems is challenging, especially due to their interconnectedness, making them vulnerable to various cyber threats. The rising tide of IoT botnets, especially, presents a unique challenge. This has urgently increased the need for Intrusion Detection research. Modern Intrusion Detection approaches often employ Machine Learning for effective results. Feature Selection is extremely important while creating Machine Learning Classification models to avoid overfitting and poor performance. This paper focuses on running a Feature Selection study on the Bot-IoT dataset provided by UNSW to increase the accuracy of a ML model. The paper tests 5 types of Feature Selection methods, from Filter- based, Wrapper-based and Embedded methods, combined with two distinct ensemble classifiers: Random Forest + Adaboost and XGBoost. Each combination is tested with the dataset, and the accuracy is compared to find the most effective and versatile feature selection method that can assist both Stacking and Voting- type Ensemble classifiers. The results show that Karl Pearson can provide the best accuracy when applied to both Ensemble Classifiers. 2024 IEEE. Creator An entity primarily responsible for making the resource Fernando C.A.; Thomas R.; Mary Anita E.A.; Lapina M. Source A related resource from which the described resource is derived Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/InC460750.2024.10649035" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC460750.2024.10649035</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203794329&amp;doi=10.1109%2FInC460750.2024.10649035&amp;partnerID=40&amp;md5=b9a9bc897de0bf16506a87418ef7662b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203794329&amp;doi=10.1109%2fInC460750.2024.10649035&amp;partnerID=40&amp;md5=b9a9bc897de0bf16506a87418ef7662b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038365-2 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Fernando C.A., CHRIST (Deemed to be University), Bangalore, India; Thomas R., CHRIST (Deemed to be University), Bangalore, India; Mary Anita E.A., CHRIST (Deemed to be University), Bangalore, India; Lapina M., Institute of Digital Development North-Caucasus Federal University Stavropol, Russian Federation