High-Throughput Privacy-Preserving GRU Network with Homomorphic Encryption-Reference-Cited by-同舟云学术

High-Throughput Privacy-Preserving GRU Network with Homomorphic Encryption

Published:2023-06-18 Issue: Volume: Page:
ISSN:
Container-title:2023 International Joint Conference on Neural Networks (IJCNN)
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Author:

Wang Zeyu¹,Ikeda Makoto¹

Affiliation:

1. The University of Tokyo,Department of Electrical Engineering and Information Systems,Tokyo,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10190990/10190992/10191194.pdf?arnumber=10191194

Reference24 articles.

1. Cryptodl: Deep neural networks over encrypted data;hesamifard;ArXiv,2017

2. Layer Normalization;ba;ArXiv,2016

3. CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy;dowlin;Proceedings of the 33rd International Conference on International Conference on Machine Learning - Volume 48,0

4. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

5. Improved Bootstrapping for Approximate Homomorphic Encryption

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1. High-throughput and fully-pipelined ciphertext multiplier for homomorphic encryption;IEICE Electronics Express;2024-03-25

2. Toward Bootstrapping-Free Homomorphic Encryption-Based GRU Network for Text Classification;IEEE Access;2024

3. High-throughput and fully-pipelined ciphertext multiplier for homomorphic encryption;IEICE ELECTRON EXPR;2024

4. High-Throughput Key Switching Accelerator for Homomorphic Encryption;2023 International Conference on IC Design and Technology (ICICDT);2023-09-25