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COVID-19 malicious domain names classification

  • Published:2022-10 Issue: Volume:204 Page:117553
  • ISSN:0957-4174
  • Container-title:Expert Systems with Applications
  • language:en
  • Short-container-title:Expert Systems with Applications

Author:

Mvula Paul K.ORCID,Branco PaulaORCID,Jourdan Guy-Vincent,Viktor Herna L.ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference46 articles.

1. VisualPhishNet: Zero-day phishing website detection by visual similarity;Abdelnabi,2020

2. Phishing dynamic evolving neural fuzzy framework for online detection “zero-day” phishing email;ALmomani;Indian Journal of Science and Technology,2013

3. A comprehensive survey of AI-enabled phishing attacks detection techniques;Basit;Telecommunication Systems,2021

4. A gentle introduction to random forests, ensembles, and performance metrics in a commercial system;Benyamin,2012

5. Enriching word vectors with subword information;Bojanowski;Transactions of the Association for Computational Linguistics,2017

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1. A review on lexical based malicious domain name detection methods;Annals of Telecommunications;2024-06-13

2. Research on malicious domain name detection method based on deep learning;Proceedings of the 2024 3rd International Conference on Cryptography, Network Security and Communication Technology;2024-01-19

3. Survival strategies of two changing societies’ customary consultative assemblies: The orahua of Nias and the kerapatan adaik of West Sumatra;Cogent Arts & Humanities;2023-12-14

4. Recent Advancements in Machine Learning for Cybercrime Prediction;Journal of Computer Information Systems;2023-10-24

5. Machine Learning-Based Detection of Phishing in COVID-19 Theme-Related Emails and Web Links;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2023-10-01
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