Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2024.2415797
Real-time phishing URL detection framework using knowledge distilled ELECTRA
K. S. Jishnu
; Department of Computing Technologies, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur Campus, Chengalpattu, Tamilnadu, India
B. Arthi
; Department of Computing Technologies, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur Campus, Chengalpattu, Tamilnadu, India
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* Dopisni autor.
Sažetak
The rise of cyber threats, particularly URL-based phishing attacks, has tarnished the digital age
despite its unparalleled access to information. These attacks often deceive users into disclosing confidential information by redirecting them to fraudulent websites. Existing browser-based
methods, predominantly relying on blacklist approaches, have failed to effectively detect phishing attacks. To counteract this issue, we propose a novel system that integrates a deep learning
model with a user-centric Chrome browser extension to detect and alert users about potential
phishing URLs instantly. Our approach introduces a Knowledge Distilled ELECTRA model for URL
detection and achieves remarkable performance metrics of 99.74% accuracy and a 99.43% F1-
score on a diverse dataset of 450,176 URLs. Coupled with the browser extension, our system
provides real-time feedback, empowering users to make informed decisions about the websites
they visit. Additionally, we incorporate a user feedback loop for continuous model enhancement. This work sets a precedent by offering a seamless, robust, and efficient solution to mitigate
phishing threats for internet users.
Ključne riječi
Distilled ELECTRA; phishing detection; URL classification; chrome extensions; real-time security
Hrčak ID:
326447
URI
Datum izdavanja:
21.10.2024.
Posjeta: 0 *