A Hybrid Approach for Malicious URL Detection Using Ensemble Models and Adaptive Synthetic Sampling

Malicious URLs pose a significant cybersecurity threat, often leading to phishing attacks, malware infections, and data breaches. Early detection of these URLs is crucial for preventing security vulnerabilities and mitigating potential losses. In this paper, we propose a novel approach for malicious...

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Hlavní autoři:	Khaled Mahmud Sujon, Rohayanti Hassan, Muhammad Edzuan Zainodin, Mohamad Aizi Salamat, Shahreen Kasim, Alde Alanda
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Society of Visual Informatics 2025-09-01
Edice:	JOIV: International Journal on Informatics Visualization
Témata:	malicious url detection url classification cybersecurity ensemble learning malware detection
On-line přístup:	https://joiv.org/index.php/joiv/article/view/4627
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