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A python based Implementation of "H.-J. Zhu et al., DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model, Neurocomputing (2017), http://dx.doi.org/10.1016/j.neucom.2017.07.030"

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fahadakbar24/android-malware-detection

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PerDRaML


The implementation is inspired from H.-J. Zhu et al., DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model, Neurocomputing (2017), http://dx.doi.org/10.1016/j.neucom.2017.07.030

Steps


1 - Installing python version 3x

https://www.python.org/downloads/release/python-380/

2 - Installing mongoDB

https://www.mongodb.com/download-center/community

3 - Installing mongoDB Compass( for viewing feature set data)

can also be installed with mongoDB setup
https://www.mongodb.com/download-center/compass

4 - creating virtual environment (to separate the project installation packages from global ones)

* cd droid-det-implementation
* https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/

5 - Installing dependencies

pip install -r requirements.txt

6 - Include sample apks under "./apks" directory

7 - run implementation

python main.py

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A python based Implementation of "H.-J. Zhu et al., DroidDet: Effective and robust detection of android malware using static analysis along with rotation forest model, Neurocomputing (2017), http://dx.doi.org/10.1016/j.neucom.2017.07.030"

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