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Existing intrusion detection systems (IDS) gather and utilize large amounts of data with irrelevant, unnecessary, and unsuitable characteristics, resulting in long detection times and low accuracy. In this paper, we present an IDS model based on a Random Forest (RF) classifier. NSL-KDD dataset is used to test the performance of the model and the satisfying performance is obtained in terms of accuracy, detection rate, and false alarm rate. The proposed model has attained an average accuracy of 99.3% and 98% for binary classification and multiclass classification, respectively. To demonstrate the efficacy of the suggested model, its accuracy was compared with some existing approaches that utilize other models such as AIDS, ELM and PCA, MapReduce-based hybrid architecture, and DRNN. <\/jats:p>","DOI":"10.1142\/s0219265921450080","type":"journal-article","created":{"date-parts":[[2022,4,11]],"date-time":"2022-04-11T12:53:46Z","timestamp":1649681626000},"source":"Crossref","is-referenced-by-count":5,"title":["Intrusion Detection System Model for IoT Networks Using Ensemble Learning"],"prefix":"10.1142","volume":"22","author":[{"given":"Umaira","family":"Ahad","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Technology, Central University of Jammu, J&K 181143, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7676-9014","authenticated-orcid":false,"given":"Yashwant","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, Central University of Jammu, J&K 181143, India"}]},{"given":"Pooja","family":"Anand","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, Central University of Jammu, J&K 181143, India"}]},{"given":"Zakir Ahmad","family":"Sheikh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, Central University of Jammu, J&K 181143, India"}]},{"given":"Pradeep Kumar","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, KIET Group of Institutions, Delhi-NCR, Ghaziabad, UP, India"}]}],"member":"219","published-online":{"date-parts":[[2022,4,9]]},"reference":[{"key":"S0219265921450080BIB001","doi-asserted-by":"publisher","DOI":"10.3390\/s21041113"},{"key":"S0219265921450080BIB002","first-page":"180","volume":"2016","author":"Andrea I.","year":"2016","journal-title":"Proc. \u2014 IEEE Symp. 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