A hybrid super learner ensemble for phishing detection on mobile devices
Abstract In today’s digital age, the rapid increase in online users and massive network traffic has made ensuring security more challenging. Among the various cyber threats, phishing remains one of the most significant. Phishing is a cyberattack in which attackers steal sensitive information, such a...
Saved in:
| Main Authors: | Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-02009-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Effective Detection Approach for Phishing URL Using ResMLP
by: S. Remya, et al.
Published: (2024-01-01) -
Phish Fighter: Self Updating Machine Learning Shield Against Phishing Kits Based on HTML Code Analysis
by: Gabriela Brezeanu, et al.
Published: (2025-01-01) -
Heuristic machine learning approaches for identifying phishing threats across web and email platforms
by: Ramprasath Jayaprakash, et al.
Published: (2024-10-01) -
An Effective Ensemble Approach for Preventing and Detecting Phishing Attacks in Textual Form
by: Zaher Salah, et al.
Published: (2024-11-01) -
Evaluating the Impact of Feature Engineering in Phishing URL Detection: A Comparative Study of URL, HTML, and Derived Features
by: Yanche Ari Kustiawan, et al.
Published: (2025-01-01)