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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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Hlavní autoři: Lapina, M. A., Лапина, М. А., Shiriaev, E. M., Ширяев, Е. М., Babenko, M. G., Бабенко, М. Г.
Médium: Статья
Jazyk:English
Vydáno: Pleiades Publishing 2024
Témata:
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
On-line přístup:https://dspace.ncfu.ru/handle/123456789/29339
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https://dspace.ncfu.ru/handle/123456789/29339

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