A Survey on Large Language Models in Phishing Detection

Phishing attacks have affected the society more than ever, therefore, detecting such attacks has been a significant challenge. This research examines the potential use of large language models (LLMs) in phishing attacks and their detection capabilities. In this context, various researches have been analyzed that explain how LLMs can be used to generate different phishing techniques, such as fake websites, emails, and text messages. In addition, the analyzed researches present various approaches to assess whether the language processing and text analysis capabilities of LLMs are effective in detecting phishing attacks. The analyses results show that LLMs are powerful tools for both attacking and developing defense mechanisms related to phishing attacks.

Authors

Institutions

Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1109/ntms65597.2025.11076905
Citations
1
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
3.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Survey on Large Language Models in Phishing Detection

Şerif Bahtıyar, Muharrem Atakan Şentürk
1 citations
Spam and Phishing Detection
3.25
article

A Survey on Large Language Models in Phishing Detection

Şerif Bahtıyar, Muharrem Atakan Şentürk
article en
1 citations

Abstract

Phishing attacks have affected the society more than ever, therefore, detecting such attacks has been a significant challenge. This research examines the potential use of large language models (LLMs) in phishing attacks and their detection capabilities. In this context, various researches have been analyzed that explain how LLMs can be used to generate different phishing techniques, such as fake websites, emails, and text messages. In addition, the analyzed researches present various approaches to assess whether the language processing and text analysis capabilities of LLMs are effective in detecting phishing attacks. The analyses results show that LLMs are powerful tools for both attacking and developing defense mechanisms related to phishing attacks.

Istanbul Technical University (TR), Istanbul University (TR)
Openalex Percentile: Top 7%
Spam and Phishing Detection
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.