What is zero knowledge convolutional neural network?
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A zero knowledge convolutional neural network (zkCNN) is a scheme that allows the owner of a CNN model to prove to others that the predictions made by the model are legitimate and accurate, without revealing any information about the model itself . This is achieved through the use of zero knowledge proof techniques, which ensure that the proof does not leak any sensitive information. zkCNN can also be used to prove the accuracy of a secret CNN model on a public dataset . Another approach is the verifiable convolution neural network (vCNN) framework, which enables a client to verify the correctness of inference results provided by an untrusted server. vCNNs utilize pairing-based zero-knowledge Succinct Non-interactive ARgument of Knowledge (zk-SNARK) schemes, which provide short proofs and quick verification .
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04 Oct 2021 4 Citations | The provided paper does not mention anything about a "zero knowledge convolutional neural network." |
3 Citations | The provided paper does not mention a "zero knowledge convolutional neural network." |
Open access•Posted Content | The paper does not mention a "zero knowledge convolutional neural network." The provided paper is about zero-shot recognition using semantic embeddings and knowledge graphs. |
Open access•Journal Article 12 Citations | The paper does not mention "zero knowledge convolutional neural network". |
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