PhishCatcher: Client-Side Defense Against Web Spoofing Attacks Using Machine Learning-Reference-Cited by-同舟云学术

PhishCatcher: Client-Side Defense Against Web Spoofing Attacks Using Machine Learning

Published:2023 Issue: Volume:11 Page:61249-61263
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ahmed Muzammil¹,Altamimi Ahmed B.²^ORCID,Khan Wilayat¹^ORCID,Alsaffar Mohammad³^ORCID,Ahmad Aakash⁴,Khan Zawar Hussain⁵^ORCID,Alreshidi Abdulrahman³^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Wah Campus, Rawalpindi, Pakistan

2. Department of Computer Engineering, University of Ha’il, Ha’il, Saudi Arabia

3. Department of Information and Computer Science, University of Ha’il, Ha’il, Saudi Arabia

4. School of Computing and Communications, Lancaster University Leipzig, Leipzig, Germany

5. Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada

Funder

Scientific Research Deanship at University of Ha’il, Saudi Arabia

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/ielx7/6287639/10005208/10155142.pdf?arnumber=10155142

Reference70 articles.

1. Cantina

2. Protect sensitive sites from phishing attacks using features extractable from inaccessible phishing URLs

3. Prophiler

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