Effectiveness of Machine Learning tools for detecting phishing attacks: A systematic review. (#436)

Authors

Morales Andía, Ciliani Iduví

Campos Echavigurin, Felix Alejandro

Ráez Martínez, Haymín Teresa

Martínez Navarro, José Antonio

Abstract

In this new technological era, there are many threats through a simple internet search, and we are daily exposed to them. A lot of people don’t know the risks and leads them to be a potential victim causing them serious consequences. The phishing is one of the most common threats that scams people all over the world. Due to that, this investigation wants to examinate the literatures existing about the based machine learning solutions for the phishing attacks. After the recompilation, that ended on 464 articles original from Scopus. But now the investigation has 30 open access articles that were carefully selected with PRISMA methodology using the inclusion and exclusion rules to guarantee that these ones are closely related to the investigated subject. The results showed that the solutions have 90% or superior precision in most of the cases. With this information, it concluded that the machine learning techniques are very effective and a good choice to affront the problem. However, there are still some aspects that has to be considered before putting it on practice.