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

被引:0
|
作者
Al-Subaiey, Abdulla [1 ]
Al-Thani, Mohammed [1 ]
Alam, Naser Abdullah [2 ]
Antora, Kaniz Fatema [2 ]
Khandakar, Amith [3 ]
Zaman, S. M. Ashfaq Uz [4 ]
机构
[1] AFG Coll Univ Aberdeen, Dept Comp Sci, Doha, Qatar
[2] Univ Liberal Arts Bangladesh, Dept Comp Sci & Engn, Dhaka, Bangladesh
[3] Qatar Univ, Coll Engn, Dept Elect Engn, Doha, Qatar
[4] Qatar Emiri Naval Forces, POB 2237, Doha, Qatar
关键词
Phishing emails; Machine learning model; Email classification; Dataset; Explainable AI; User trust; Web-based application; SPAM EMAIL; MODEL;
D O I
10.1016/j.compeleceng.2024.109625
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:23
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