Malicious URL classification using artificial fish swarm optimization and deep learning

• 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

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...