Cargando…
Malicious URL Detection Based on Associative Classification
Cybercriminals use malicious URLs as distribution channels to propagate malware over the web. Attackers exploit vulnerabilities in browsers to install malware to have access to the victim’s computer remotely. The purpose of most malware is to gain access to a network, ex-filtrate sensitive informati...
Autores principales: | Kumi, Sandra, Lim, ChaeHo, Lee, Sang-Gon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911559/ https://www.ncbi.nlm.nih.gov/pubmed/33572521 http://dx.doi.org/10.3390/e23020182 |
Ejemplares similares
-
Classification of Malicious URLs Using Machine Learning
por: Abad, Shayan, et al.
Publicado: (2023) -
BERT-Based Approaches to Identifying Malicious URLs
por: Su, Ming-Yang, et al.
Publicado: (2023) -
An intelligent identification and classification system for malicious uniform resource locators (URLs)
por: Abu Al-Haija, Qasem, et al.
Publicado: (2023) -
Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning
por: Ghaleb, Fuad A., et al.
Publicado: (2022) -
An Assessment of Lexical, Network, and Content-Based Features for Detecting Malicious URLs Using Machine Learning and Deep Learning Models
por: Aljabri, Malak, et al.
Publicado: (2022)