Design and Implementation of an Intelligent System for Cyber Fraud Detection Using Data Mining Model

Student: Joseph Chidera Okonkwo (Project, 2025)
Department of Computer Science
Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State

Abstract

Due to a rapid advancement in the electronic commerce technology, the use of credit cards has
dramatically increased. As credit card becomes the most popular mode of payment for both online
as well as regular purchases (offline), cases of fraud associated with it are also rising, where people
use other people’s credit cards or credit card details to carry out fraudulent transactions. In this
project, a sequence of operations in credit card transaction processing using Python (Jupyter
notebook as IDE) was modelled and how it can be used for the detection of frauds shown. An
algorithm initially trained with the normal behavior of a cardholder, reading the dataset of
transactions and predicting the outcome of the next transactions as fraudulent or valid.
Conclusively, this project will help battle credit card transactions frauds, stopping or reducing the
occurrences of fraudulent transactions through credit cards.

Keywords
Cyber fraud detection credit card fraud data mining machine learning intelligent system fraud prevention e-commerce security anomaly detection transaction monitoring
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