https://github.com/twseptian/simple-malware-analysis
Implementation machine learning in malware analysis
https://github.com/twseptian/simple-malware-analysis
Last synced: 3 months ago
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Implementation machine learning in malware analysis
- Host: GitHub
- URL: https://github.com/twseptian/simple-malware-analysis
- Owner: twseptian
- Created: 2019-03-28T11:15:13.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-11-16T16:25:18.000Z (almost 5 years ago)
- Last Synced: 2024-12-26T03:43:14.912Z (9 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 119 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Simple Malware Analysis using Machine Learning and how to classification with a Portable Executable File (.exe)
The author used machine learning classifier (e.g: random forest) to determine accuracy and evaluation metrics and also make a simple script executable analyzer from machine learning classifier for classify "benign" or "malicious" file.
Shortcuts
- How to analysis Endgame Ember dataset using machine learning? [here](https://github.com/twseptian/Simple-Malware-Analysis/blob/master/malware-machine-learning-random-forest.ipynb)
- How to clasify an executable file using random forest model? [here](https://github.com/twseptian/Simple-Malware-Analysis/blob/master/predict_exefile_with_our_model.ipynb)
References:
- For instalation intruction please go to ember github repository.
- Endgame Malware BEnchMark for Research (EMBER) - https://github.com/endgameinc/ember
- Dataset - https://pubdata.endgame.com/ember/ember_dataset.tar.bz2