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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Autori principali:	Lapina, M. A., Лапина, М. А., Shiriaev, E. M., Ширяев, Е. М., Babenko, M. G., Бабенко, М. Г.
Natura:	Статья
Lingua:	English
Pubblicazione:	Pleiades Publishing 2024
Soggetti:	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
Accesso online:	https://dspace.ncfu.ru/handle/123456789/29339
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