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Malicious URL classification using artificial fish swarm optimization and deep learning

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their syst...

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Bibliographic Details
Main Authors: Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, K. Nour, Mohamed, M. Asiri, Mashael, M. Al-Sharafi, Ali, Othman, Mahmoud, Motwakel, Abdelwahed
Format: Article
Language:English
English
Published: Tech Science Press 2023
Subjects:
TK7885 Computer engineering
Online Access:http://irep.iium.edu.my/101886/7/101886_Malicious%20URL%20classification%20using%20artificial%20fish%20swarm.pdf
http://irep.iium.edu.my/101886/13/101886_Malicious%20URL%20classification%20using%20artificial%20fish%20swarm_SCOPUS.pdf
http://irep.iium.edu.my/101886/
http://doi.org/10.32604/cmc.2023.031371
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http://irep.iium.edu.my/101886/7/101886_Malicious%20URL%20classification%20using%20artificial%20fish%20swarm.pdf
http://irep.iium.edu.my/101886/13/101886_Malicious%20URL%20classification%20using%20artificial%20fish%20swarm_SCOPUS.pdf
http://irep.iium.edu.my/101886/
http://doi.org/10.32604/cmc.2023.031371

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