NASS: Optimizing Secure Inference via Neural Architecture Search

30 Jan 2020Song BianWeiwen JiangQing LuYiyu ShiTakashi Sato

Due to increasing privacy concerns, neural network (NN) based secure inference (SI) schemes that simultaneously hide the client inputs and server models attract major research interests. While existing works focused on developing secure protocols for NN-based SI, in this work, we take a different approach... (read more)

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