EVA-Code

Implementation tool used in:

@article{yang2020efficient,
  title={Efficient video integrity analysis through container characterization},
  author={Yang, Pengpeng and Baracchi, Daniele and Iuliani, Massimo and Shullani, Dasara and Ni, Rongrong and Zhao, Yao and Piva, Alessandro},
  journal={IEEE Journal of Selected Topics in Signal Processing},
  volume={14},
  number={5},
  pages={947--954},
  year={2020},
  doi={10.1109/JSTSP.2020.3008088},
  publisher={IEEE}
}

Authors

• Daniele Baracchi ([email protected])
• Dasara Shullani ([email protected])

License

Copyright (C) 2021 Università degli studi di Firenze

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

Testing

Requirements

• tested with Python 3.8.10 and the following packages:

bokeh==2.3
scikit-learn==0.24
xmltodict==0.12

Data

• uncompress ./code/Containers.tar.gz

Replicate results

• run ./code/run_all.sh

cd code
bash run_all.sh

The table results are accessible at the following paths:

• Table I: results/tampering-detector/no-os/no-lr/non-SN-acc.txt

• Table III: results/tampering-classifier/no-os/no-lr/non-SN-cm.html

• Table IV: results/tampering-classifier/os/no-lr/non-SN-cm.html

• Table VI: results/blind-classifier/os/no-lr/blind-cm.html

• Table V: run the get_global_accuracy.py script as in

  python get_global_accuracy.py results/tampering-detector/no-os/no-lr/Facebook.pkl
  python get_global_accuracy.py results/tampering-detector/no-os/no-lr/Tiktok.pkl 
  python get_global_accuracy.py results/tampering-detector/no-os/no-lr/Weibo.pkl 
  python get_global_accuracy.py results/tampering-detector/no-os/no-lr/Youtube.pkl 
  

NOTE: Be aware that the overall results will need 4.3 GB of storage.