How to utilize zero-knowledge proof scheme in artificial intelligence algorithm?
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Zero-knowledge proof schemes can be utilized in artificial intelligence algorithms to address concerns regarding privacy, integrity, and reproducibility. These schemes provide a way to verify the correctness and accuracy of machine learning models without revealing sensitive information about the model itself . By using zero-knowledge proofs, the owner of a machine learning model can convince others that the model computes a specific prediction or achieves high accuracy on public datasets, while keeping the model details confidential . Additionally, zero-knowledge proof algorithms can be applied to secure authentication systems, preventing the exchange of personal information between the claimant and verifier . This ensures that data is protected from unauthorized sources, changes, and authentication issues . Overall, zero-knowledge proof schemes offer a promising approach to enhance the security and privacy of artificial intelligence algorithms.
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Open access•Posted Content | The provided paper does not discuss the utilization of zero-knowledge proof scheme in artificial intelligence algorithms. |
| The paper discusses the use of zero-knowledge proof protocols in machine learning models to ensure the integrity and accuracy of predictions without revealing sensitive information about the model. | |
| The provided paper does not discuss how to utilize zero-knowledge proof schemes in artificial intelligence algorithms. | |
| The provided paper does not discuss how to utilize zero-knowledge proof schemes in artificial intelligence algorithms. |
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