pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing

doi:doi:10.57702/f8p499cp

pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing

We propose a new approach for privacy-preserving and verifiable convolutional neural network (CNN) testing in a distrustful multi-stakeholder environment.

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Jiasi Weng, Jian Weng, Gui Tang, Anjia Yang, Ming Li, Jia-Nan Liu (2024). Dataset: pvCNN: Privacy-Preserving and Verifiable Convolutional Neural Network Testing. https://doi.org/10.57702/f8p499cp

DOI retrieved: December 16, 2024

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2201.09186
Author	Jiasi Weng
More Authors	Jian Weng Gui Tang Anjia Yang Ming Li Jia-Nan Liu