Sufficiency of Ensemble Machine Learning Methods for Phishing Websites Detection-Reference-Cited by-同舟云学术

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Sufficiency of Ensemble Machine Learning Methods for Phishing Websites Detection

Published:2022 Issue: Volume:10 Page:124103-124113
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wei Yi¹^ORCID,Sekiya Yuji²

Affiliation:

1. Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

2. Security Informatics Education and Research Center, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09963966.pdf?arnumber=9963966

Reference45 articles.

1. Ensemble Methods in Machine Learning

2. Phishing website detection using novel machine learning fusion approach

3. SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective

4. Application of deep learning to cybersecurity: A survey

Cited by 11 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. Detection of phishing URLs with deep learning based on GAN-CNN-LSTM network and swarm intelligence algorithms;Signal, Image and Video Processing;2024-06-17

2. An Investigation of AI-Based Ensemble Methods for the Detection of Phishing Attacks;Engineering, Technology & Applied Science Research;2024-06-01

3. Enhancing Phishing Detection Through Ensemble Learning and Cross-Validation;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

4. Classification of Phishing Webpages using Supervised Machine Learning Algorithms;2024 15th Annual Undergraduate Research Conference on Applied Computing (URC);2024-04-24

5. Machine Learning-Powered Defense Against Phishing Websites;2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS);2024-02-24

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