Novel interpretable and robust web-based AI platform for phishing email detection

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...

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Bibliographic Details
Published in:Computers & electrical engineering 2024-12, Vol.120, p.109625, Article 109625
Main Authors: Al-Subaiey, Abdulla, Al-Thani, Mohammed, Abdullah Alam, Naser, Antora, Kaniz Fatema, Khandakar, Amith, Uz Zaman, SM Ashfaq
Format: Article
Language:English
Subjects:
Dataset
Email classification
Explainable AI
Machine learning model
Phishing emails
User trust
Web-based application
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Summary: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.
ISSN:0045-7906
DOI:10.1016/j.compeleceng.2024.109625