Fraud Detection in E-Commerce Transactions Using Machine Learning and AI

Fraud Detection in E-Commerce Transactions Using Machine Learning and AI

1. Vls Prathyusha

Dept of cse

Asst prof

KITS AKSHAR INSTITUTE   OF TECHNOLOGY

2) Dr. E. Raghava Chaitanya

Osmania University

Hyderabad.

3) Paparao Areti

Research Scholar

A.U TDR-HUB           Andhra University  Visakhapatnam

Assistant professor

Malla Reddy  Institute Of Technology & Science Hyderabad

4) Arun S

Assistant Professor

Department of Computer Science

Sree Ayyappa College, Eramallikkara, Chengannur Kerala

5) G HARISH

Asst professor

Dept of commerce

Excellencia Group of institutions Hyderabad

6) M.K.GEEDTHA,M.E.,

ASSISTANT PROFESSOR,

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

7. Sadiya Afsheen

Assistant professor

CSE

Jaya Prakash Narayan college of Engineering

Abstract

The worldwide growth of e-commerce transactions has made fraud detection into a pressing issue that needs resolution. Existing rule-based fraud detection technologies cannot keep up with new deceptive methods that emerge in the market. Through the combination of artificial intelligence (AI) and machine learning (ML) techniques the detection of fraud has become more efficient by processing large datasets to spot complex criminal activities. The analysis investigates supervised and unsupervised learning models as well as deep learning algorithms and anomaly detection frameworks for their application in fraud detection systems. This assessment verifies real-time fraud detection strengths of multiple models in addition to their operational capacity for dynamic fraud patterns. The document explores both privacy matters and ethical issues linked to AI-based fraud detection systems. Research shows that superheroes in the field of AI achieve excellent results because their combination of various detection methods diminishes false alarms while strengthening fraud protection systems. The research boosts current e-commerce fraud mitigation studies because it reveals recent progress and prospective artificial intelligence-based fraud detection trends.

Keywords:

Fraud detection, machine learning, AI, e-commerce, anomaly detection, cybersecurity.