# State of the Art: Content-based and Hybrid Phishing Detection

arXiv: https://arxiv.org/abs/2101.12723 · HTML: https://mlsanity.com/paper/2101.12723/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 19 references that are in the map.
- First posted on arXiv 29 Jan 2021.

## Builds on (most cited first, 1 of 1)

- [Look Before You Leap: Detecting Phishing Web Pages by Exploiting Raw URL And HTML Characteristics](https://mlsanity.com/paper/2011.04412/) (2020)

## Abstract (arXiv)

Phishing attacks have evolved and increased over time and, for this reason, the task of distinguishing between a legitimate site and a phishing site is more and more difficult, fooling even the most expert users. The main proposals focused on addressing this problem can be divided into four approaches: List-based, URL based, content-based, and hybrid. In this state of the art, the most recent techniques using web content-based and hybrid approaches for Phishing Detection are reviewed and compared.