The code corresponds to the paper “Validating the integrity of Convolutional Neural Network predictions based on Zero-Knowledge Proof“
- This library implements a zero-knowledge scheme for proving/verifying the integrity of CNN predictions.
- Please follow libsnark's instructions to build a zero-knowledge proof runtime environment and install the required core libraries. https://github.com/scipr-lab/libsnark
- The src folder contains the example CNN model prediction integrity circuit we designed.
- The sample code for extracting the computational information of the CNN model prediction process is shown in File Model_Extract.py .