Journal of Cybersecurity and Information Management JCIM 2690-6775 2769-7851 10.54216/JCIM https://www.americaspg.com/journals/show/1780 2019 2019 Sudan University of Science and Technology, Faculty of Science, Khartoum, Sudan Othman Al Basheer Gaziantep University, Department of Mathematics, Gaziantep, Turkey Murat Ozcek Big data has become an integral part of modern businesses, but its management and protection present numerous challenges, such as securing sensitive information from unauthorized access, preventing data breaches, and ensuring data integrity. This work investigated applying a machine learning (ML) approach to tackling the challenges of information security and management in big data environments. We present an ML framework that leverages a supervised learning strategy to detect anomalies, classify big data, and predict potential security threats. We also investigate the implementation of this framework and its potential benefits, such as reducing false positives and improving detection rates. Our experimental analysis in public datasets demonstrates the effectiveness of our approach in improving information security and management in big data environments. 2023 2023 58 66 10.54216/JCIM.110106 https://www.americaspg.com/articleinfo/2/show/1780