Enhancing cybersecurity: A review and comparative analysis of convolutional neural network approaches for detecting URL-based phishing attacks-Reference-Cited by-同舟云学术

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Enhancing cybersecurity: A review and comparative analysis of convolutional neural network approaches for detecting URL-based phishing attacks

Published:2024-06 Issue: Volume:8 Page:100533
ISSN:2772-6711
Container-title:e-Prime - Advances in Electrical Engineering, Electronics and Energy
language:en
Short-container-title:e-Prime - Advances in Electrical Engineering, Electronics and Energy

Author:

Nanda Manika,Saraswat Mala^ORCID,Sharma Pankaj Kumar

Publisher

Elsevier BV

Reference46 articles.

1. Machine learning based phishing detection from URLs;Sahingoz;Expert. Syst. Appl.,2019

2. Intelligent methods for accurately detecting phishing websites;Abuzuraiq,2020

3. Web phishing detection techniques: a survey on the state-of-the-art, taxonomy and future directions;Vijayalakshmi;IET Networks,2020

4. Phishing website detection based on multidimensional features driven by deep learning;Yang;IEEE Access,2019

5. PhishHaven—An efficient real-time AI phishing URLs detection system;Sameen;IEEE Access,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integrating machine learning for sustaining cybersecurity in digital banks;Heliyon;2024-09

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