Malware-Detection-Using-ML-And-DL-Techniques
- This is a Python program to train Malware Detection ML Model and check if a given file is a probable MALWARE or not!
- I have implemented using
NOTE: Don't run any files inside malwares folder, as these are actual malwares taken from GitHub.
Requirements (installable via pip)
- For running CLI app:
- For running Streamlit app:
- For training your own model:
What I used?
- Scikit-learn - Scikit-learn (formerly scikits.learn and also known as sklearn) is a free software machine learning library for the Python programming language.
- RandomForestClassifier
- ExtraTreesClassifier
- Malware Dataset - The raw data here was obtained from the malware security partner of Meraz'18 - Annual Techno Cultural festival of IIT Bhilai, the said raw data constituted malware and legitimate files.
- Streamlit - for GUI - Streamlit is an open-source app framework for Machine Learning and Data Science teams.
- Flask - for distributed system - Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.
How to run the program?
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Download this GitHub repository
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Download & Install requirements
-
Run Streamlit app
streamlit run streamlit_app.py