DOI: https://doi.org/10.1016/j.future.2019.11.034

README.txt

Help file to run the project written in Python 2.7 and 3.0.

Dr. Rahim Taheri did this implementation. 
Dr. Rahim Taheri, Dr. Mohammad Shojafar and Dr. Meysam Ghahramani helped on idea brainstorming and documentation. 
Reza Javidan, Zahra Pooranian and Mauro Conti helped in English correction and leading the team.

If you need any help on the code, feel free to drop a message to

Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
Dr. Rahim Taheri <taheri.rahim@gmail.com> 

Step of the running project:

Label_Flipping_Paper_with_Feature_Selection.py is for label flipping code with feature selection method

Label_Flipping_Paper_without_Feature_Selection.py is for label flipping code without feature selection method

The comparisons are embedded in the code.

We used three datasets which can be obtained through the links on the paper. 

Note: you need to preprocess and clean the dataset before implementation. 


I will be glad to cite our paper with the following details in your research papers:

R. Taheri, M. Ghahramani, R. Javidan, M. Shojafar, Z. Pooranian, M. Conti, "Similarity-based Android Malware Detection Using Hamming Distance of Static Binary Features", Elsevier, Future Generation Computer Systems, (FGCS), Vol. 105, pp. 230-247, April 2020. 

DOI: https://doi.org/10.1016/j.future.2019.11.034