Skip to content

Automatic analysis of malware behavior using machine learning

Notifications You must be signed in to change notification settings

bienkma/DetectionMalwareBehavior

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

About

I created the project for test K-Neighbors, SVM, Navie-Bayes, Random forest Classifier. About it: - DATA SET = CSDMC_API_Train.csv append with CSDMC_API_TestData.csv. Files download http://csmining.org/index.php/malicious-software-datasets-.html - Test data = 1/4 Training data - in csv file. 1 and 0 is label Malware or Not Malware

  • Model created by Random Forest (RF) Algorithms. A web base on Flask allow client upload file .csv for scan fast virus with model base RF Algorithm.

Deploy

  • Run train:
python detector.py
  • Create model:
python predict.py
  • Run web api
python webapi.py

User access to http://ip_webapi/ upload file .csv example 1.csv with content contain 2 API/System call windows: SetThreadPriority LocalAlloc LocalFree ...

Notes: You can use IDA Pro export API/System call of on programe save to .csv file.

About

Automatic analysis of malware behavior using machine learning

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages