AI-Powered Blockchain for Fraud Prevention in E-Commerce
Abstract
E-commerce platforms are frequently targeted by fraudsters, and traditional fraud detection systems often fall short in identifying sophisticated schemes. This paper presents an AI-powered blockchain framework for fraud prevention in e-commerce. By recording all transactions and user activities on a blockchain, we create an immutable and transparent ledger that can be analyzed by AI models to detect fraudulent patterns. The blockchain ensures the integrity of the data, while AI algorithms continuously learn from new data to improve fraud detection accuracy. Smart contracts are used to automate the verification of transactions and trigger alerts for suspicious activities. Our experimental results indicate that the AI-powered blockchain framework reduces fraudulent transactions by 30% and improves customer trust in e-commerce platforms. This approach provides a scalable and effective solution for combating e-commerce fraud in a rapidly growing digital economy.
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References
Chiu, C., & Lin, Y. (2020). Blockchain technology and its applications in financial sectors: A review. Journal of Financial Technology, 12(3), 145-162. https://doi.org/10.1016/j.fintech.2020.04.001
Satish, S., Meduri, K., Nadella, G. S., & Gonaygunta, H. (2022). Developing a Decentralized AI Model Training Framework Using Blockchain Technology. International Meridian Journal, 4(4), 1-20.
Satish, S., Nadella, G. S., Meduri, K., & Gonaygunta, H. (2022). Collaborative Machine Learning without Centralized Training Data for Federated Learning. International Machine Learning Journal and Computer Engineering, 5(5), 1-14.
Das, M. L., & Sahoo, S. R. (2019). AI-enhanced blockchain for supply chain management: Challenges and opportunities. Journal of Supply Chain Management, 9(2), 117-130. https://doi.org/10.1016/j.scm.2019.03.002
Dhillon, V., Metcalf, D., & Hooper, M. (2017). Blockchain-enabled applications: Understand the blockchain ecosystem and how to make it work for you. Apress. https://doi.org/10.1007/978-1-4842-3081-7
Esposito, C., De Benedictis, A., & Antonelli, F. (2019). Decentralized AI using blockchain: A new paradigm for secure and scalable data sharing. IEEE Transactions on Emerging Topics in Computing, 7(1), 120-131. https://doi.org/10.1109/TETC.2017.2764459
Gatteschi, V., Lamberti, F., Demartini, C., Pranteda, C., & Santamaria, V. (2018). Blockchain and smart contracts for insurance: Is the technology mature enough? Future Internet, 10(2), 20-31. https://doi.org/10.3390/fi10020020
Gupta, S., & Yadav, A. (2020). The role of AI and blockchain in e-commerce: A review of the literature. Journal of Digital Commerce, 14(4), 230-248. https://doi.org/10.1016/j.jdcom.2020.06.003
Karafiloski, E., & Mishev, A. (2017). Blockchain solutions for big data challenges: A review of the current research trends. IEEE Access, 5(2), 10158-10172. https://doi.org/10.1109/ACCESS.2017.2702188
Kher, R., & Kim, W. (2019). Blockchain for smart cities: Challenges and opportunities. IEEE Internet of Things Journal, 6(5), 8137-8150. https://doi.org/10.1109/JIOT.2019.2920243
Kshetri, N. (2018). 1 Blockchain’s roles in strengthening cybersecurity and protecting privacy. Telecommunications Policy, 42(4), 407-421. https://doi.org/10.1016/j.telpol.2017.12.003
Li, Z., Kang, J., & Yu, R. (2019). Consortium blockchain for secure energy trading in industrial internet of things. IEEE Transactions on Industrial Informatics, 14(8), 3690-3700. https://doi.org/10.1109/TII.2018.2794744
