mpasco/MalbehavD-V1
Public datasets of malware and benign executable files (Windows EXE files). The dataset can be used by cybersecurity researchers focusing on the area of malware detection. It is suitable for training and testing both machine learning and deep learning algorithms.
This dataset helps cybersecurity researchers develop and test tools that automatically identify malicious Windows executable files. It provides sequences of API calls, extracted from both malware and legitimate software, that can be used to train and evaluate machine learning models. Cybersecurity analysts and researchers working on malware detection systems would use this.
No commits in the last 6 months.
Use this if you are building or evaluating machine learning models to classify Windows executable files as either benign or malicious based on their behavioral characteristics.
Not ideal if you need raw executable files for static analysis or if your focus is on non-Windows operating systems.
Stars
24
Forks
2
Language
—
License
MIT
Category
Last pushed
Jul 25, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mpasco/MalbehavD-V1"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
rednaga/APKiD
Android Application Identifier for Packers, Protectors, Obfuscators and Oddities - PEiD for Android
0xfke/Malware-Detection-and-Analysis-using-Machine-Learning
Malware🦠Detection and Analysis using Machine Learning (MDAML) is designed to provide users with...
rieck/malheur
A Tool for Automatic Analysis of Malware Behavior
AFAgarap/malware-classification
Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support...
Kiinitix/Malware-Detection-using-Machine-learning
Anomaly based Malware Detection using Machine Learning (PE and URL)