A Boosting-Based Hybrid Feature Selection and Multi-Layer Stacked Ensemble Learning Model to Detect Phishing Websites-Reference-Cited by-同舟云学术

A Boosting-Based Hybrid Feature Selection and Multi-Layer Stacked Ensemble Learning Model to Detect Phishing Websites

Published:2023 Issue: Volume:11 Page:71180-71193
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kalabarige Lakshmana Rao¹,Rao Routhu Srinivasa²^ORCID,Pais Alwyn R.³,Gabralla Lubna Abdelkareim⁴^ORCID

Affiliation:

1. AI Research Laboratory, GMR Institute of Technology, Rajam, India

2. Department of Computer Science and Engineering, Gandhi Institute of Technology and Management, Visakhapatnam, Andhra Pradesh, India

3. Department of Computer Science and Engineering, Information Security Research Laboratory, National Institute of Technology, Surathkal, Karnataka, India

4. Department of Computer Science and Information Technology, College of Applied, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia

Funder

Princess Nourah Bint Abdulrahman University

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/ielx7/6287639/10005208/10177158.pdf?arnumber=10177158

Reference50 articles.

1. Phishing Detection: A Literature Survey

2. Detection of phishing websites using an efficient feature-based machine learning framework

3. Intelligent Methods for Accurately Detecting Phishing Websites

4. The Best Features Selection Method and Relevance Variable for Web Phishing Classification

5. CANTINA+

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