Private machine learning classification based on fully homomorphic encryption

IEEE Transactions on Emerging Topics in Computing(2020)

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摘要
Machine learning classification is an useful tool for trend prediction by analyzing big data. As supporting homomorphic operations over encrypted data without decryption, fully homomorphic encryption (FHE) contributes to machine learning classification without leaking user privacy, especially in the outsouring scenario. In this paper, we propose an improved FHE scheme based on HElib, which is a FH...
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关键词
Decision trees,Encryption,Additives,Switches,Protocols,Privacy
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