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This repository follows the paper "Crystal Ball: From Innovative Attack to Attack Effectiveness Classifier", IEEE Access, 2021.

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Android-crystal-ball

This repository follows the Crystal Ball paper.

The results of the attacks against the VT scanners are presented in the VT_results folder.

The version of the Drebin model was taked from: https://github.com/MLDroid/drebin

The implementation of Sec-SVM was kindly given to us by S2Lab: https://s2lab.cs.ucl.ac.uk/projects/intriguing/

The DNN (basic DNN model from the repository) was taken from: https://github.com/deqangss/adv-dnn-ens-malware

The re-implemenation of the FM model (based on https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8931539) used the implementation of Drebin. The changes are described in FM.txt.

The malicious apks can be obtained from the Drebin formal website: https://www.sec.cs.tu-bs.de/~danarp/drebin/

An extended version of the benign dataset can be found in: https://drive.google.com/file/d/1cDU-_K4q3fphwMlef7nJjZuIH7lPt3mN/view?usp=sharing

The code of the evasion attacks can be viewed in the MB attacks folder.

Citation

@article{berger2021crystal,
  title={Crystal Ball: From Innovative Attacks to Attack Effectiveness Classifier},
  author={Berger, Harel and Hajaj, Chen and Mariconti, Enrico and Dvir, Amit},
  journal={IEEE Access},
  year={2021},
  publisher={IEEE}
}

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This repository follows the paper "Crystal Ball: From Innovative Attack to Attack Effectiveness Classifier", IEEE Access, 2021.

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  • Python 77.1%
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