https://github.com/hayesall/maliciousportableexecutabledetection
Determining whether a portable executable file (.exe) is malicious or benign with comparative results for multiple ML algorithms: AdaBoost, DT, GNB, GradientBoosting, KNN, RF.
https://github.com/hayesall/maliciousportableexecutabledetection
classification machine-learning security
Last synced: 8 months ago
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Determining whether a portable executable file (.exe) is malicious or benign with comparative results for multiple ML algorithms: AdaBoost, DT, GNB, GradientBoosting, KNN, RF.
- Host: GitHub
- URL: https://github.com/hayesall/maliciousportableexecutabledetection
- Owner: hayesall
- License: mit
- Created: 2017-05-15T23:48:35.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-05-15T23:49:14.000Z (about 9 years ago)
- Last Synced: 2025-02-05T09:35:07.229Z (over 1 year ago)
- Topics: classification, machine-learning, security
- Language: Python
- Homepage:
- Size: 57 MB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE