Fingerprinting toolbox is a library that allows embedding and extracting fingerprints into the relational data.
⚓ This repository contains the official implementation of NCorr-FP. See: NCorr-FP
You can use the toolbox by cloning this repository.
$ git clone https://github.com/tanjascats/fingerprinting-toolbox.git
For fingerprint insertion, we can define the scheme with the parameter gamma and bit-length of a fingerprint. The number of modified rows in the data will then be approx. #rows/gamma (TIP: use gamma to control the amount of modifications in the data).
scheme = Universal(gamma=2, fingerprint_bit_length=64)
After the scheme is initialized, we can embedd the fingerprint using our (owner's) secret key and specifying recipient's ID:
fingerprinted_data = scheme.insertion("my_data.csv", secret_key=4370315727, recipient_id=0)
For the fingerprint extraction, we provide the suspicious data and the secret key used for embedding:
suspect = scheme.detection("suspicious_data.csv", secret_key=4370315727)
For more examples and detailed explanations check out the notebook example.ipynb.
The toolbox is in its early stage, but actively developing, so you can either:
- Report the issues at Issues or
- Contact me by email: TSarcevic@sba-research.org for questions, suggestions or issues
- Pull requests are welcome