Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection

TL;DR

This paper presents a highly accurate, interpretable, and real-time web-based AI platform for phishing email detection, addressing limitations of prior research by using a large public dataset and explainability features.

Contribution

It introduces a novel high-performance machine learning model with integrated Explainable AI, deployed as a practical web application for real-world phishing detection.

Findings

Achieved an F1 score of 0.99 on a large public dataset.

Developed a user-trust-enhancing explainable AI component.

Created a real-time web-based phishing email detection platform.

Abstract

Phishing emails continue to pose a significant threat, causing financial losses and security breaches. This study addresses limitations in existing research, such as reliance on proprietary datasets and lack of real-world application, by proposing a high-performance machine learning model for email classification. Utilizing a comprehensive and largest available public dataset, the model achieves a f1 score of 0.99 and is designed for deployment within relevant applications. Additionally, Explainable AI (XAI) is integrated to enhance user trust. This research offers a practical and highly accurate solution, contributing to the fight against phishing by empowering users with a real-time web-based application for phishing email detection.