jm55dlsu/thesis

Behavior-Based Malware Detection using GBDTs

Evaluation and Comparison of Boosted ML Models in Behavior-Based Malware Detection

Choa, de Veyra, Escalona, Fortiz

This is a repository for the Thesis "Evaluation and Comparison of Boosted ML Models in Behavior-Based Malware Detection".

It contains the Jupyter notebook files and datasets used for the development of the study.

Tested on:

1. Windows
2. Linux (Debian-based)

Pre-requisite Software:

1. Python 3.11.x
2. Anaconda/Conda

Kindly install these before proceeding to the next step.

Library Installation:

1. Once the two software is installed open Anaconda Prompt in your computer and navigate to the local copy of the repository in your computer.
2. Once navigated, type install.bat for Windows or install.sh for Linux. The script will begin the installation of the necessary libraries for your Conda environment.
3. Once completed, you can now begin exploring the thesis project files.

How to run:

1. Open Anaconda Prompt
2. Navigate to the location of the GitHub repository on your computer.
3. Type jupyter notebook
4. To terminate jupyter, simply Ctrl+C on the Anaconda Prompt.

Tips for running on Linux:

1. Install Anaconda as shown here.
2. Once completed, run Anaconda Terminal (assuming conda config --set auto_activate_base False ) by typing soure <PATH_TO_ANACONDA>/bin/activate

CUDA Toolkit

Make sure you have installed the CUDA Toolkit in your machine to ensure that GPU (CUDA-specific) is supported. Do note that this may replace (downgrade) your GPU driver.

LightGBM GPU Support

• Download the latest GCC
• Download the latest CMake
• Download the Boost v1.56.0
• Follow the guide