Inference and conversion method for encrypted deep neural network model
Ku, Yu-Te Hsu, Chih-Fan Chen, Wei-Chao Liu, Feng-Hao Chang, Ming-Ching Hung, Shih-Hao
Ku, Yu-Te
Hsu, Chih-Fan
Chen, Wei-Chao
Liu, Feng-Hao
Chang, Ming-Ching
Hung, Shih-Hao
Supervisor
Department
Computer Science
Embargo End Date
Type
Patent
Date
2025
License
Language
English
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Abstract
An inference method for encrypted deep neural network model is executed by a computing device and includes: encoding a message according to a quantization parameter to generate a plaintext, encrypting the plaintext according to a private key to generate a ciphertext, sending the ciphertext to a deep neural network model to generate a ciphertext result, decrypting the ciphertext result according to the private key to generate a plaintext result, and decoding the plaintext result according to the quantization parameter to generate an inference result.
Citation
“US20250080320A1 - Inference and conversion method for encrypted deep neural network model - Google Patents.”. [Online]. Available: https://patents.google.com/patent/US20250080320A1/en
Source
US Patent App. 18/409,595, 2025
Conference
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Publisher
Google Patent