Abstract
In the year 2022, mobile devices became the target of many Ransomware attacks preventing users from accessing their files. The purpose of this article was to present the research preferences in the detection of this type of Malware based on Machine Learning. For this reason, a systematic review was carried out that provided indicators to measure detection accuracy, prevention measures and statistical data that show the most used algorithms for tracking Ransomware on mobile devices, such as: Support Vector Machine (24%), Random Forest Regression (18%), k-NN (15%), and J48 Decision Tree (12%).
| Translated title of the contribution | Systematic Literature Review: Machine Learning for Ransomware Detection on Mobile Devices |
|---|---|
| Original language | Spanish |
| Pages (from-to) | 341-353 |
| Number of pages | 13 |
| Journal | RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao |
| Volume | 2022 |
| Issue number | E54 |
| State | Published - 1 Jan 2022 |
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