Ensemble Learning-Powered URL Phishing Detection: A Performance Driven Approach
With the rapid growth in the usage of the Internet, criminals have found new ways to engage in cyber-attacks. The most common and widespread attack is URL phishing. The proposed system focuses on improving phishing website detection using feature selection and ensemble learning. This model uses two...
Saved in:
| Main Authors: | Shougfta Mushtaq, Tabassum Javed, Mazliham Mohd Su’ud |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MMU Press
2024-06-01
|
| Series: | Journal of Informatics and Web Engineering |
| Subjects: | |
| Online Access: | https://journals.mmupress.com/index.php/jiwe/article/view/881 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Mutual information based logistic regression for phishing URL detection
by: Vajratiya Vajrobol, et al.
Published: (2024-01-01) -
APPLYING THE AUTOENCODER MODEL FOR URL PHISHING DETECTION
by: Dang Thi Mai
Published: (2024-12-01) -
Machine Learning-Enabled Attacks on Anti-Phishing Blacklists
by: Wenhao Li, et al.
Published: (2024-01-01) -
Real-time phishing URL detection framework using knowledge distilled ELECTRA
by: K. S. Jishnu, et al.
Published: (2024-10-01) -
Unveiling the Efficacy of AI-based Algorithms in Phishing Attack Detection
by: Tajamul Shahzad, et al.
Published: (2024-06-01)