This project focuses on leveraging machine learning algorithms to distinguish between normal and malicious files enhancing cybersecurity measures. The primary goal is to develop an automated system capable of detecting malware with high accuracy thus reducing the reliance on manual analysis and improving response times to potential threats.
Here're some of the project's best features:
- Accuracy in detection for corrupt and normal files
- Reliable
Technologies used in the project:
- Python
- Random Forest Classifier Algorithm
- VS Code
- Reference to various papers and websites
- Any.run website & Kaggle datasets