# Phishing Detection Leveraging Machine Learning and Deep Learning: A Review

arXiv: https://arxiv.org/abs/2205.07411 · HTML: https://mlsanity.com/paper/2205.07411/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2022.

## Built on by (most cited first, 3 of 3)

- [KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection](https://mlsanity.com/paper/2403.02253/) (2024)
- [Novel Interpretable and Robust Web-based AI Platform for Phishing Email Detection](https://mlsanity.com/paper/2405.11619/) (2024)
- [Multimodal Large Language Models for Phishing Webpage Detection and Identification](https://mlsanity.com/paper/2408.05941/) (2024)

## Abstract (arXiv)

Phishing attacks trick victims into disclosing sensitive information. To counter rapidly evolving attacks, we must explore machine learning and deep learning models leveraging large-scale data. We discuss models built on different kinds of data, along with their advantages and disadvantages, and present multiple deployment options to detect phishing attacks.