Welcome to the GitHub page for the ongoing research on detecting malware in Android-based smartphones using artificial intelligence! In this project, we are developing machine learning and deep learning algorithms to identify and classify malware in Android applications.
Repository Name: android-malware-detection
Overview: This repository contains the code and resources for the ongoing research on malware detection in Android-based smartphones using machine learning and deep learning algorithms. The goal of this project is to develop accurate and efficient techniques to detect malware in Android applications, and contribute to the field of cybersecurity.
Folder Structure:
data: This folder contains the datasets used for training and testing the machine learning and deep learning algorithms. It includes both benign and malicious Android applications.
code: This folder contains the source code for the machine learning and deep learning algorithms, including implementations of Random Forest, Naive Bayes, and Support Vector Machines. The code is written in Python and utilizes popular machine learning libraries such as scikit-learn and TensorFlow.
models: This folder contains the trained machine learning and deep learning models that have been developed for malware detection. These models can be used for inference on new Android applications.