Volume 11 , Issue 2 , PP: 36-46, 2023 | Cite this article as | XML | Html | PDF | Full Length Article
Taif Khalid Shakir 1 * , Rabah Scharif 2 , Manal M. Nasir 3
Doi: https://doi.org/10.54216/JCIM.110204
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.
Blockchain , Security , Machine Learning , Big data , Secure Networks
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