A Differential Privacy Random Forest Method of Privacy Protection in Cloud

This paper proposes a new random forest classification algorithm based on differential privacy protection. In order to reduce the impact of differential privacy protection on the accuracy of random forest classification, a hybrid decision tree algorithm is proposed in this paper. The hybrid decision...

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Bibliographic Details
Published in2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC) pp. 470 - 475
Main Authors Lv, Chaoxian, Li, Qianmu, Long, Huaqiu, Ren, Yumei, Ling, Fei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2019
Subjects
Classification algorithms
Decision trees
differential privacy
Forestry
Prediction algorithms
Privacy
privacy protection
random forest
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Summary:This paper proposes a new random forest classification algorithm based on differential privacy protection. In order to reduce the impact of differential privacy protection on the accuracy of random forest classification, a hybrid decision tree algorithm is proposed in this paper. The hybrid decision tree algorithm is applied to the construction of random forest, which balances the privacy and classification accuracy of the random forest algorithm based on differential privacy. Experiment results show that the random forest algorithm based on differential privacy can provide high privacy protection while ensuring high classification performance, achieving a balance between privacy and classification accuracy, and has practical application value.
DOI:10.1109/CSE/EUC.2019.00093