Aloraini, Fatimah  ORCID: https://orcid.org/0000-0001-5494-0661, Saxena, Neetesh ORCID: https://orcid.org/0000-0002-6437-0807, Bertino, Elisa, Das, Ashok Kumar and Choo, Kim-Kwang Raymond
2026.
FastTrick: socially-engineered phishing e-mail detection using hashing trick.
IEEE Transactions on Knowledge and Data Engineering
10.1109/TKDE.2026.3705635
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Abstract
Despite anti-phishing solutions, recent statistics from the Anti-Phishing Working Group and several other government agencies and security companies show that the problem of phishing is far from being solved. In this paper, we present a content-based machine learning model that can distinguish phishing e-mails from legitimate ones and overcome the challenge of sparse representations to a significant extent. The model implements the hashing trick, which is a technique to encode categorical features, instead of traditional dictionary-based methods to generate vector representations of e-mail bodies. A comparison of supervised machine learning algorithms, Support Vector Machine (SVM), Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and Logistic Regression (LR), is performed to find the best model to identify phishing e-mail, including those spread during Coronavirus the (COVID-19). The obtained results show that the SVM outperforms in all cases. The proposed approach successfully demonstrates that using feature hashing improves the feature extraction process in terms of feature vector size (requires only 8% of the dataset's original size) and extraction time compared to previous content-based detection models.
| Item Type: | Article |
|---|---|
| Date Type: | Published Online |
| Status: | In Press |
| Schools: | Schools > Computer Science & Informatics |
| Additional Information: | RRS applied |
| Publisher: | Institute of Electrical and Electronics Engineers |
| ISSN: | 1041-4347 |
| Date of First Compliant Deposit: | 16 June 2026 |
| Date of Acceptance: | 13 June 2026 |
| Last Modified: | 03 Jul 2026 15:00 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/187566 |
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