• Ashish
• Sudarshan K
• M Suhas
• Sreenith
• Vachan

In the growing world of e-commerce, fraud continues to be a critical concern, impacting businesses and customers alike. This paper introduces an AI-based fraud detection framework to identify fraudulent activities in online transactions in real time.This system utilizes AI algorithms that analyze transaction details to determine whether the behavior is authentic or potentially deceptive.By incorporating modules for data preprocessing, feature extraction, anomaly detection, and classification, the system aims to reduce false positives and adapt to evolving fraud patterns. The hybrid model, trained on public and synthetic datasets, achieved high accuracy and low latency, demonstrating viability for deployment in live e-commerce environments

E-commerce, Fraud Detection, Machine Learning, Anomaly Detection, Real-Time Security, AI in Finance

"AI-POWERED E-COMMERCE FRAUD DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.110-112, July-2025, Available :http://www.jetir.org/papers/JETIRGX06020.pdf

"AI-POWERED E-COMMERCE FRAUD DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp110-112, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06020.pdf