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 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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Institutions

Publication Details

Journal
Computers & Electrical Engineering
Published
2024-09-10
DOI
https://doi.org/10.1016/j.compeleceng.2024.109625
Citations
25
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
19.48
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article

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

Amith Abdullah Khandakar, SM Ashfaq Uz Zaman, Naser Abdullah Alam, Abdulla Al-Subaiey et al.
25 citations
Computers & Electrical Engineering
Spam and Phishing Detection
19.48
article

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

Amith Abdullah Khandakar, SM Ashfaq Uz Zaman, Naser Abdullah Alam, Abdulla Al-Subaiey, Mohammed Al-Thani, Kaniz Fatema Antora
article en
25 citations

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.

Computers & Electrical EngineeringVol. 120
University of Liberal Arts Bangladesh (BD), Gulf English School (QA), Qatar University (QA)
Openalex Percentile: Top 1%
Spam and Phishing Detection
19.48
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Novel interpretable and robust web-based AI platform for phishing email detection — Amith Abdullah Khandakar, SM Ashfaq Uz Zaman, et al. · Computers & Electrical Engineering (2024) | TGRS Research Map | TGRS