pNitesh01 / SSE-TERM-PROJECT

CS6570 course project

SSE-TERM-PROJECT (CS6570 course project)

AI-Based Malware Detection

Overview

This project focuses on malware detection using machine learning techniques. It employs various classifiers to identify obfuscated malware and evaluates their performance through different metrics.

Dataset

The dataset used for this project is Obfuscated-MalMem2022.

Research Paper

For more detailed information, refer to the research paper: AI-Based Malware Detection.

Libraries Used

• pandas
• numpy
• seaborn
• matplotlib
• scikit-learn

Features

• Data Preprocessing: Cleans and prepares the dataset for modeling.
• Exploratory Data Analysis (EDA): Analyzes malware distribution.
• Model Training: Implements and evaluates various classifiers:
  • Random Forest
  • Naive Bayes
  • Decision Tree
  • SVM
  • Logistic Regression
  • KNN
• Ensemble Models: Combines multiple classifiers using stacking techniques.

Evaluation

Models are evaluated using:

• F1 Score
• Precision
• Recall
• Accuracy
• Confusion Matrix