Primer: Fast Private Transformer Inference on Encrypted Data

It is increasingly important to enable privacy-preserving inference for cloud services based on Transformers. Post-quantum cryptographic techniques, e.g., fully homomorphic encryption (FHE), and multi-party computation (MPC), are popular methods to support private Transformer inference. However, exi...

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Vydané v:	2023 60th ACM/IEEE Design Automation Conference (DAC) s. 1 - 6
Hlavní autori:	Zheng, Mengxin, Lou, Qian, Jiang, Lei
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.07.2023
Predmet:	Computational modeling Cryptographic Protocol Cryptography Design automation Fully Homomorphic Encryption Multi-party computation Natural language processing Private Inference Solids Transformer Transformers
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