Detecting phishing websites through improving convolutional neural networks with Self-Attention mechanism
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Published:2024-01
Issue:
Volume:
Page:102643
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ISSN:2090-4479
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Container-title:Ain Shams Engineering Journal
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language:en
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Short-container-title:Ain Shams Engineering Journal
Author:
Said YahiaORCID,
Alsheikhy Ahmed A.ORCID,
Lahza HusamORCID,
Shawly Tawfeeq
Subject
General Engineering
Reference38 articles.
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2. A comprehensive survey of AI-enabled phishing attacks detection techniques;Basit;Telecommun Syst,2021
3. B. Liang, M. SU, W. YOU, W. Shi and G. Yang, “Cracking classifiers for evasion: a case study on the google's phishing pages filter,” in Proceedings of the 25th International Conference on World Wide Web, Montréal Québec Canada, pp. 345-356, 2016.
4. Q. Cui, V. J. Guy, V. B. Gregor, C. Russell and Q. V. Iosif, “Tracking phishing attacks over time,” in Proceedings of the 26th International Conference on World Wide Web, Republic and Canton of Geneva, Switzerland, pp. 667-676, 2017.