Authors

Prof. B. O. Omijeh

NCC Professorial Chair, University of Port Harcourt, Rivers State, Nigeria

Eberechi Victor

University of Port Harcourt, Port Harcourt, Nigeria

Aji Jacob Onu

Centre for Information and Telecommunication Engineering, University of Port Harcourt, Rivers State, Nigeria

Abstract

This form of fraud called phishing is a form of threat that involves exploiting users and organizations through malicious or deceptive emails and web URLS. In this study, explored are some of the application of artificial intelligence data analysis and machine learning techniques applied in the detecting, preventing and mitigating the prevalence attacks particularly phishing here, diverse dataset have been leveraged to develop high accuracy models that can help detect legitimate and malicious emails or legitimate and malicious URL, here we extract features like certain keywords, certain behaviors, URL blacklisting, URL shortening services, etc NLP (natural language processing) methods like TF-IDF are used to enhance model accuracy and precision algorithms like random forest decision tree extra tree and XGboost are used. Our result demonstrates high accuracy and how important the use of multiple algorithms can be. This research considers the potential of AI-driven solutions in mitigating fraud with particular respect to phishing.

Keywords

Phishing URL Phishing Email Algorithm TF-IDF Classifier

Citation of this Article

Prof. B. O. Omijeh, Eberechi Victor, & Aji Jacob Onu. (2025). An AI Approach to Mitigating Online Fraud, Phishing as a Case Study. International Current Journal of Engineering and Science - ICJES, 4(7), 18-25. Article DOI: https://doi.org/10.47001/ICJES/2025.407002

Licence Copyright (c) 2026 International Current Journal of Engineering and Science. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

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