Multi-cloud privacy-preserving logistic regression

Multi-cloud privacy-preserving logistic regression

Clouds can significantly reduce the cost and time of business solutions. However, cloud services introduce significant security and privacy challenges when they process sensitive information. For instance, a dataset for machine learning could contain delicate information that traditional encryption...

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書誌詳細
主要な著者:	Babenko, M. G., Бабенко, М. Г.
フォーマット:	Статья
言語:	English
出版事項:	Springer Science and Business Media Deutschland GmbH 2022
主題:	Cloud security Secure multi-party computation Homomorphic encryption Privacy-preserving logistic regression Residue number system (RNS) Quality control
オンライン･アクセス:	https://dspace.ncfu.ru/handle/20.500.12258/18617
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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