Identification and Analysis of Phishing Website based on Machine Learning Methods-Reference-Cited by-同舟云学术

Identification and Analysis of Phishing Website based on Machine Learning Methods

Published:2022-05-21 Issue: Volume: Page:
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Container-title:2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE)
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Author:

Alkawaz Mohammed Hazim¹,Joanne Steven Stephanie²,Mohammad Omar Farook³,Gapar Md Johar Md⁴

Affiliation:

1. Management and Science University,Faculty of Information Sciences & Engineering,Shah Alam,Selangor,Malaysia

2. Management and Science University,School of Graduates Studies,Shah Alam,Selangor,Malaysia

3. Al-Hadba University College,Computer Technology Engineering,Mosul,Iraq

4. Management and Science University,Information Technology and Innovation Centre,Shah Alam,Selangor,Malaysia

Funder

Management and Science University

Publisher

IEEE

Link

Reference28 articles.

2. Leverage Website Favicon to Detect Phishing Websites;kang leng chiew;Hindawi Security and Communication Networks,2017

3. Phishing Detection using RDF and Random Forests;vamsee muppavarapu;The International Arab Journal of Information Technology,2018

4. Phishing page detection via learning classifiers from page layout feature;jian mao;EURASIP Journal on Wireless Communications and Networking,2019

5. Phishing Website Detection using Machine Learning Algorithms;rishikesh mahajan;International Journal of Computer Applications,2018

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3. Hybrid Obfuscation of Encryption;Coding Theory Essentials;2023-08-30

4. Phishing Prediction on Website Updates with Novel Features Through Machine Learning;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

5. Hybrid Feature-Based Machine Learning Method for Phishing URL Detection;2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC);2023-05-26