High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks

High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks

Due to legal restrictions or restrictions related to companies' internal information policies, businesses often do not trust sensitive information to public cloud providers. One of the mechanisms to ensure the security of sensitive data in clouds is homomorphic encryption. Privacy-preserving ne...

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Главные авторы:	Lapina, M. A., Лапина, М. А., Shiriaev, E. M., Ширяев, Е. М., Babenko, M. G., Бабенко, М. Г.
格式:	Статья
語言:	English
出版:	Pleiades Publishing 2024
主題:	Convolutional neural networks Spatial complexity Cryptography Differential privacy High Speed Ho-momorphic encryptions Homomorphic-encryptions Information policy Legal restriction Multiplication algorithms Scalar multiplication Privacy preserving Neural-networks Convolution
在線閱讀:	https://dspace.ncfu.ru/handle/123456789/29339
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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