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FuadBinAkhter/Malware-detection-of-Android-using-native-and-custom-permissions-with-ML-model-Optimization

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Overview

Due to the rapid expansion of Android apps and their global appeal in the smartphone market, it has become an accessible and straightforward target for malware. Although numerous updates have been made to fix the vulnerabilities of the Android operating system, malware applications have also evolved and upgraded in response to this change. This work investigates and classifies benign and malicious Android permissions as features for machine learning (ML) classifiers.

Requirements

  • Python
  • Numpy
  • Pandas
  • Seaborn
  • Matplotlib

Dataset

Contains permissions extracted from more than 29000 benign & malware Android apps released between 2010-2019. (https://archive.ics.uci.edu/dataset/722/naticusdroid+android+permissions+dataset)

Code

You will find the codes of this project inside the "Codes" folder.

You need to download the datasets from corresponding source (please follow the 'Dataset' section for source) and keep them in a folder of your google drive. You will have to rename the folder and set the 'path' value according to your folder location in the drive.

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Utilizing Machine learning (ML) classifiers to detect benign and malicious Android permissions

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