IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 8 Issue 4 Computer Science and Engineering English July - August 2020 N N Y 2020 08 01 Computer Sciences A Stacked Ensemble Framework for Detecting Malicious Insiders English Y 294 298 Abolaji B. Akanbi English Y Adewale O. Adebayo English N Sunday A. Idowu English N Ebunoluwa E. Okediran English N https://doi.org/10.21276/ijircst.2020.8.4.8 One of the mainstream strategies identified for detecting Malicious Insider Threat (MIT) is building stacking ensemble Machine Learning (ML) models to reveal malevolent insider activities through anomalies in user activities. However, most anomalies found by these learning models were not malicious because MIT was treated as a single entity, whereas there are various forms of this threat with their own distinct signature. To address this deficiency, this study focused on designing a stacked ensemble framework for detecting malicious insider threat which utilizes a one scenario per algorithm strategy. A model that can be used to test the framework was proposed. English Ensemble Learning, Malicious Insider Threat, Machine Learning, Stacked Generalization. https://ijircst.org/abstract.php?article_id=531