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Published Paper Details:
ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING AND BLOCKCHAIN
Authors
DR.D.Loganathan,A.Agalya,A.K.Rohith malar,V.Satheeshwaran
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Keywords
Online Payment Fraud Machine Learning LightGBM Classifier Higher Dimensional Triage Model Blockchain Technology Secure Transactions Razorpay Integration Fraud Detection System Real-time Transaction Monitoring
Abstract
The proliferation of e-commerce and digital payments has brought unprecedented convenience but has simultaneously increased the exposure of financial systems to fraudulent activities. In this paper, we present a comprehensive framework for online payment fraud detection that synergistically integrates machine learning (ML), blockchain technology, and real-time payment gateway processing (Razorpay). This multi-layered system not only aims to predict and prevent fraudulent transactions with high accuracy but also ensures the integrity, traceability, and security of transaction records.At the core of the framework is a Light Gradient Boosting Machine (LightGBM) classifier, enhanced with a Higher Dimensional Triage Model. This triage model leverages advanced feature transformation, dimensional expansion techniques, and anomaly scoring to improve the model's sensitivity to rare but impactful fraudulent patterns. By embedding the triage mechanism, the system gains improved capability in handling class imbalance, feature sparsity, and subtle fraudulent behavior, which are common challenges in financial fraud detection.To safeguard transaction logs and model outputs from tampering, we integrate a private, permissioned blockchain ledger using a lightweight, customizable consensus mechanism. Each transaction--whether flagged as fraudulent or legitimate--is cryptographically recorded in the blockchain, ensuring data immutability, accountability, and forensic traceability.
IJCRT's Publication Details
Unique Identification Number - IJCRT25A5706
Paper ID - 287818
Author type - Indian Author
Page Number(s) - o828-o834
Pubished in - Volume 13 | Issue 5 | May 2025
DOI (Digital Object Identifier) -
No Of Downloads - 65
Author Country - India, 641107, coimbatore, coimbatore, 641107, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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DR.D.Loganathan,A.Agalya,A.K.Rohith malar,V.Satheeshwaran, "ONLINE PAYMENT FRAUD DETECTION USING MACHINE LEARNING AND BLOCKCHAIN", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 5, pp.o828-o834, May 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A5706.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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