Machine learning algorithm for a homomorphic encrypted data set

JIA Chunfu; WANG Yafei; CHEN Yang; SUN Mengjie; GE Fengyi

doi:10.16511/j.cnki.qhdxxb.2020.25.011

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Journal of Tsinghua University(Science and Technology) ›› 2020, Vol. 60 ›› Issue (6) : 456-463. DOI: 10.16511/j.cnki.qhdxxb.2020.25.011

SPECIAL SECTION: TRUSTED COMPUTING AND INFORMATION SECURITY

Machine learning algorithm for a homomorphic encrypted data set

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Abstract

The continuous development of big data requires that data be stored and analyzed in the cloud, which leads to privacy leakage of sensitive data. This paper presents a machine learning classification algorithm for homomorphic encrypted data sets. Firstly, preprocess the data set to meet the requirements of homomofphic encryption. The encrypted data set is then sorted by protocol and classified. Finally, the classification results are obtained. The client can then upload encrypted data and ensure that the server will not get any sensitive information. A homomorphic encryption algorithm is used to ensure that the server can still perform required operations on the ciphertext. Tests show that this scheme can provide accurate, useful results with Bayes, hyperplane and decision tree classifiers.

Key words

privacy-preserving / homomorphic encryption / classification algorithm / operations on encrypted data

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JIA Chunfu, WANG Yafei, CHEN Yang, SUN Mengjie, GE Fengyi. Machine learning algorithm for a homomorphic encrypted data set[J]. Journal of Tsinghua University(Science and Technology). 2020, 60(6): 456-463 https://doi.org/10.16511/j.cnki.qhdxxb.2020.25.011

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