Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions

Saved in:
Bibliographic Details
Published in:IEEE Access Vol. 10; pp. 36429 - 36463
Main Authors: Nguyet Quang Do, Ali Selamat, Ondrej Krejcar, Enrique Herrera-Viedma, Hamido Fujita
Format: Journal Article
Language:Japanese
Published: Institute of Electrical and Electronics Engineers (IEEE) 01.01.2022
Subjects:
Artificial intelligence
Biology
Bot Detection
Botany
Botnet Detection
Characterization and Detection of Android Malware
Computer Networks and Communications
Computer science
Context (archaeology)
Cybersecurity
Data science
deep learning
Detection
Detection and Prevention of Phishing Attacks
Electrical engineering. Electronics. Nuclear engineering
Empirical research
Epistemology
FOS: Computer and information sciences
FOS: Philosophy, ethics and religion
Information Systems
Intrusion Detection
Machine learning
Network Intrusion Detection and Defense Mechanisms
Paleontology
Philosophy
Phishing
Phishing detection
Physical Sciences
Signal Processing
Taxonomy (biology)
The Internet
TK1-9971
World Wide Web
ISSN:2169-3536
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
ISSN:2169-3536
DOI:10.1109/access.2022.3151903