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- W4313005487 abstract "Most previous studies leverage homomorphic encryptions to execute arithmetic operations (e.g., summation, average) on encrypted data. However, these schemes are designed for a specific application environment and just achieve secure computation of a limited number of functions. Therefore, we propose a new privacy-preserving multifunctional data handling scheme with three main contributions. Firstly, it can efficiently complete plenty of rich, secure arithmetic operations through homomorphic encryption techniques to destroy the one-to-one relationship between data and its source. Secondly, it can resist differential attacks launched by the data processing entity by adding random noise. Meanwhile, it enables data analyzing entities to obtain accurate results by removing random noise. Ultimately, we conduct the security analysis, performance analysis, and comparison. These analyses show that the proposed scheme can preserve data privacy and differential privacy and is efficient regarding computation cost and communication overhead." @default.
- W4313005487 created "2023-01-05" @default.
- W4313005487 creator A5021119779 @default.
- W4313005487 creator A5085600894 @default.
- W4313005487 date "2022-01-01" @default.
- W4313005487 modified "2023-09-30" @default.
- W4313005487 title "A Universal Lightweight Privacy-Preserving Multifunctional Data Handling Scheme" @default.
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- W4313005487 doi "https://doi.org/10.1007/978-981-19-8445-7_17" @default.
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