International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | UPI Fraud Detection using Machine Learning |
|---|---|
| ABSTRACT | With the rapid growth of digital payments in India, Unified Payments Interface (UPI) has become a widely used platform for fast and convenient transactions. However, the increase in UPI usage has also led to a significant rise in fraudulent activities such as unauthorized transactions, phishing attacks, and account takeovers. This project presents an automated UPI Fraud Detection System using Machine Learning techniques to identify and prevent fraudulent transactions in real time.The proposed system utilizes historical UPI transaction data and applies machine learning classification algorithms to distinguish between legitimate and fraudulent transactions. Important transaction features such as transaction amount,frequency, device type, location, and time patterns are analyzed. The trained model is integrated into a backend system that predicts fraud probability and alerts users or banks when suspicious activity is detected. The system demonstrates high accuracy and reliability, making it suitable for real-time fraud prevention in digital payment platforms. |
| AUTHOR | DR. SHIVAMURTHY R C, PROF. AKSHATHA M, NITIN S, RAMYA S, SUPRAJ K, VAIBHAVI H S Department of Computer Science and Engineering, Maharaja Institute of Technology Mysore Affiliated to Visvesvaraya Technological University (VTU), Belagavi, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401023 |
| pdf/23_UPI Fraud Detection using Machine Learning.pdf | |
| KEYWORDS | |
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