Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning

Web applications have become ubiquitous for many business sectors due to their platform independence and low operation cost. Billions of users are visiting these applications to accomplish their daily tasks. However, many of these applications are either vulnerable to web defacement attacks or creat...

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Bibliographische Detailangaben
Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 22; H. 9; S. 3373
Hauptverfasser:	Alsaedi, Mohammed, Ghaleb, Fuad, Saeed, Faisal, Ahmad, Jawad, Alasli, Mohammed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 28.04.2022 MDPI
Schlagworte:	Algorithms Analysis Computational linguistics Computer hackers Computer Security cyber threat intelligence cybersecurity Cyberterrorism Database searching Decision making ensemble learning Identity theft Intelligence Internet of Things internet security Internet software Internet/Web search services Language processing Machine Learning malicious URLs Natural language interfaces Neural Networks, Computer Online searching Phishing Spyware Technology application URLs Web applications Websites ensemble learning cyber threat intelligence malicious URLs internet security cybersecurity
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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