Privacy-Preserved Approximate Classification Based on Homomorphic Encryption

Privacy-Preserved Approximate Classification Based on Homomorphic Encryption

Privacy is a crucial issue for outsourcing computation, which means that clients utilize cloud infrastructure to perform online prediction without disclosing sensitive information. Homomorphic encryption (HE) is one of the promising cryptographic tools resolving privacy issue in this scenario. Howev...

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Bibliographic Details
Main Authors:	Xiaodong Xiao, Ting Wu, Yuanfang Chen, Xingyue Fan
Format:	Article
Language:	English
Published:	MDPI AG 2019-10-01
Series:	Mathematical and Computational Applications
Subjects:	privacy homomorphic encryption machine learning gradient boosting decision tree
Online Access:	https://www.mdpi.com/2297-8747/24/4/92

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