主催: 電気・情報関係学会九州支部連合大会委員会
会議名: 2020年度電気・情報関係学会九州支部連合大会
回次: 73
開催地: オンライン開催（大会本部：九州産業大学）
開催日: 2020/09/26 - 2020/09/27
Using the high-performance cloud computing infrastructure to accelerate training and inference of deep learning neural networks is becoming mainstream. However, privacy leakage risk also increases because user data for training and inference must be plaintext in the cloud. To achieve a privacy-preserving neural network processing on a public cloud, we propose Homomorphic Encryption Neural Network （HE-NN）, which can perform training and inference with encrypted data. For evaluation, we show the inference accuracy and processing time profiling of the proposed HE-NN.
