aspg-2-1780-1791417286 20261007235446 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2023 11 1 Othman Al Basheer Sudan University of Science and Technology, Faculty of Science, Khartoum, Sudan Murat Ozcek Gaziantep University, Department of Mathematics, Gaziantep, Turkey 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 58 66 1780 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.110106 https://www.americaspg.com/journal/2/article/1780 https://www.americaspg.com/storage/11683730707.pdf