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arXiv · 2405.11619

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

Abdulla Al-Subaiey·Mohammed Al-Thani·Naser Abdullah Alam·Kaniz Fatema Antora·Amith Khandakar·SM Ashfaq Uz Zaman
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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.

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Abdulla Al-Subaiey, Mohammed Al-Thani, Naser Abdullah Alam, Kaniz Fatema Antora, Amith Khandakar, SM Ashfaq Uz Zaman. 2024-05-19. Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection. https://doi.org/10.1016/j.compeleceng.2024.109625

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