TanayBhadula/malware-image-detection
A deep learning project which uses a method that converts malware .bytes files into gray-scale images and uses a CNN deep learning model to classify the converted malware image and identify the malware family it belongs to.
This helps security analysts quickly identify malware families without traditional, time-consuming methods. It takes malware binary files, converts them into gray-scale images, and then classifies them into known malware families using visual patterns. Security operations teams or malware researchers dealing with large volumes of suspicious files would find this useful.
No commits in the last 6 months.
Use this if you need to rapidly classify unknown malware samples into known families, bypassing the complexities of static or dynamic analysis.
Not ideal if you require an in-depth behavioral analysis of malware or need to identify brand-new, previously unseen malware types.
Stars
35
Forks
4
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 06, 2022
Commits (30d)
0
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