Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions
Current security cloud practices can successfully protect stored data and data in transit, but they do not keep the same protection during data processing. The data value extraction requires decryption, creating critical exposure points. As a result, privacy-preserving techniques are emerging as a c...
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| Главные авторы: | , |
|---|---|
| Формат: | Статья |
| Язык: | English |
| Опубликовано: |
Institute of Electrical and Electronics Engineers Inc.
2024
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| Темы: | |
| Online-ссылка: | https://dspace.ncfu.ru/handle/123456789/29245 |
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