Locally private estimation of conditional probability distribution for random forest in multimedia applications

Xiaotong Wu, Muhammad Bilal, Xiaolong Xu, Houbing Song

Abstract: Highlights•Conditional probability distribution estimation is applied to random forest for multimedia classification applications.•A naive private algorithm that directly perturbs the values of each attribute and label in a random forest is proposed.•An improved algorithm of probability distribution estimation with lower communication cost and better accuracy is proposed.•Experimental results show that the proposed private random forest has better performance than the existing decision models.