industry, to help them understand the state of the art and facilitate their own research and practical applications. We also discuss practical issues in system design, open research challenges, and point out some important directions for future research.'
author:
- 'Doyen Sahoo[^1], Chenghao Liu[^2], and Steven C.H. Hoi [^3] [^4]'
bibliography:
- 'mud\_bib.bib'
title: 'Malicious URL Detection using Machine Learning: A Survey'
---

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Malicious URL Detection, Machine Learning, Online Learning, Internet security, Cybersecurity

Introduction
============

The advent of new communication technologies has had tremendous impact in the growth and promotion of businesses spanning across many applications including online-banking, e-commerce, and social networking. In fact, in today’s age it is almost mandatory to have an online presence to run a successful venture. As a result, the importance of the World Wide Web has continuously been increasing. Unfortunately, the technological advancements come coupled with new sophisticated techniques to attack and scam users. Such attacks include rogue websites that sell counterfeit goods, financial fraud by tricking users into revealing sensitive information which eventually lead to theft of money or identity, or even installing malware in the user’s system. There are a wide variety of 