https://github.com/shreyansh26/linux-malware-detection-through-symbol-table-mining
Implementation of the paper "Malware Detection Through Mining Symbol Table of Linux Executables" by Jinrong Bai, Yanrong Yang, Shiguang Mu and Yu Ma
https://github.com/shreyansh26/linux-malware-detection-through-symbol-table-mining
data-mining elf hacktoberfest malware-detection symbol-table
Last synced: 7 months ago
JSON representation
Implementation of the paper "Malware Detection Through Mining Symbol Table of Linux Executables" by Jinrong Bai, Yanrong Yang, Shiguang Mu and Yu Ma
- Host: GitHub
- URL: https://github.com/shreyansh26/linux-malware-detection-through-symbol-table-mining
- Owner: shreyansh26
- License: mit
- Created: 2018-12-20T07:25:23.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-10-17T19:23:49.000Z (almost 5 years ago)
- Last Synced: 2025-01-14T02:14:21.344Z (9 months ago)
- Topics: data-mining, elf, hacktoberfest, malware-detection, symbol-table
- Language: Jupyter Notebook
- Homepage:
- Size: 8.62 MB
- Stars: 3
- Watchers: 3
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Malware Detection Through Mining Symbol Table of Linux Executables
## Requirements
1. Python 2.7
2. Java 8.0+
## To run the system
1. Put all the ELF files to analyse in the `elf` folder.
2. Run `python run_system.py`
## Description
* The list of all function calls extracted from the ELF files dataset (Malware and benign) is in **functions.txt**.
* The function calls above the threshold (currently at 300) are present in **functions_less.txt**.
* The dataset on which the models were trained is **results2.csv**.
* The saved models are in **models/**.
* The code for model evaluation on the test set is in **system/**.