Android Malware Detection - RFC

This repository contains the code for the Machine Learning and Data Analysis course at the University of Genoa. The course is part of the Master's degree in Computer Science.

Intro

During this project, we have used Random Forest Classification to create a model that will detect if an Android application is malware or not.

Dataset

The dataset consists of 328 columns, including 326 binary features, which are possible Android application permissions, and another one which is label, if the application is malware or benign.

Presentation File

To showcase our Android Random Forest classification project, we have utilized this file. The project's primary objective is to accurately classify Android applications as either benign or malicious.

This dataset is distributed under the terms of the MIT License.