Skip to main navigation Skip to search Skip to main content

Revisión Sistemática de la Literatura: Machine Learning para la Detección de Ransomware en Dispositivos Móviles

Research output: Contribution to journalArticlepeer-review

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 contributionSystematic Literature Review: Machine Learning for Ransomware Detection on Mobile Devices
Original languageSpanish
Pages (from-to)341-353
Number of pages13
JournalRISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
Volume2022
Issue numberE54
StatePublished - 1 Jan 2022

Fingerprint

Dive into the research topics of 'Revisión Sistemática de la Literatura: Machine Learning para la Detección de Ransomware en Dispositivos Móviles'. Together they form a unique fingerprint.

Cite this