aspg-2-1785-1791951647 20261014042047 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cybersecurity and Information Management JCIM 2769-7851 2690-6775 2023 11 2 Taif Khalid Shakir College de Paris, France Rabah Scharif Applied Engineering Department, Institute of Applied Technology, UAE Manal M. Nasir Gwinnett Technical College, 5150 Sugarloaf Pkwy, Lawrenceville, GA 30043, USA As technology continues to evolve, the importance of information security and management becomes more crucial than ever. Blockchain and machine learning (ML) are two technologies that are gaining increasing attention in this field. Blockchain provides a secure and decentralized platform for storing and sharing information, while ML can help detect patterns and anomalies in data to identify potential security threats. This paper proposes a blockchain-based ML system for securing information management by providing an automated service for detecting anomalies in Ethereum transactions. The system utilizes a blockchain network to securely store and manage data, and ML algorithms to analyze and detect potential security threats. We present a case study using the Ethereum Fraud Detection Dataset to demonstrate the effectiveness of our proposed system in detecting fraudulent transactions. Our results show that our system outperforms traditional ML algorithms in terms of accuracy (99.55%), and F1-score (99.98%), highlighting the potential of blockchain-based ML for improving information security and management in various industries. 2023 36 46 1785 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCIM.110204 https://americaspg.com/journal/2/article/1785 https://americaspg.com/storage/01740765370.pdf