ShoumikSaha/DRSM
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness (ICLR 2024)
This project helps cybersecurity analysts and security engineers accurately identify malicious software. It takes in raw executable files and determines if they are benign or malware, providing a robust classification even when facing subtle alterations. This tool is designed for security professionals who need reliable malware detection for threat analysis and system protection.
No commits in the last 6 months.
Use this if you need a highly dependable and robust system for classifying executable files as malware or benign, with strong guarantees against minor modifications designed to evade detection.
Not ideal if you're looking for a simple, off-the-shelf malware scanner that doesn't require model training or fine-tuning, or if your primary focus is on detecting zero-day exploits rather than robust classification of known-type malware.
Stars
14
Forks
5
Language
Python
License
GPL-3.0
Category
Last pushed
Apr 22, 2024
Commits (30d)
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