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

• URL: http://arxiv.org/abs/2405.11619v1
• Date: Sun, 19 May 2024 17:18:27 GMT
• Title: Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection
• Authors: Abdulla Al-Subaiey, Mohammed Al-Thani, Naser Abdullah Alam, Kaniz Fatema Antora, Amith Khandakar, SM Ashfaq Uz Zaman,
• Abstract summary: Phishing emails pose a significant threat, causing financial losses and security breaches. This study proposes a high-performance machine learning model for email classification. The model achieves a f1 score of 0.99 and is designed for deployment within relevant applications.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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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