Enhancing Phishing URL Detection: A Comparative Study of Machine Learning Algorithms-Reference-Cited by-同舟云学术

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Enhancing Phishing URL Detection: A Comparative Study of Machine Learning Algorithms

Published:2023-09-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2023 Asia Conference on Artificial Intelligence, Machine Learning and Robotics
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Author:

Alsarhan Ayoub¹^ORCID,Igried Bashar¹^ORCID,Bani Saleem Raad Mohammad¹^ORCID,Alauthman Mohammad²^ORCID,Aljaidi Mohammad³^ORCID

Affiliation:

1. Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology, The Hashemite University, Jordan

2. Department of Information Security, University of Petra, Jordan

3. Faculty of Information Technology, Zarqa University, Jordan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3625343.3625348

Reference17 articles.

1. Zuraiq , A. A. and Alkasassbeh , M . Phishing detection approaches . IEEE , City , 2019 . Zuraiq, A. A. and Alkasassbeh, M. Phishing detection approaches. IEEE, City, 2019.

2. Phishing Website Detection With Semantic Features Based on Machine Learning Classifiers

3. A Review of Deep Learning Security and Privacy Defensive Techniques

4. HTMLPhish: Enabling Phishing Web Page Detection by Applying Deep Learning Techniques on HTML Analysis

5. A New Method for Detection of Phishing Websites: URL Detection

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