
A framework for secure and efficient private inference of deep neural network models by partitioning the model layers between a trusted execution environment (TEE) and a GPU accelerator, balancing privacy preservation and computational efficiency.


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secure-and-efficient-private-inference-of-deep-neural-network-models-using-layer-partitioning-and-trusted-execution-environments


Secure and Efficient Private Inference of Deep Neural Network Models using Layer Partitioning and Trusted Execution Environments
