DPWeka: Achieving Differential Privacy in WEKA
Srinidhi Katla, Depeng Xu, Yongkai Wu, Qiuping Pan, Xintao Wu · 2017
In this paper, we present DPWeka, a differentially private prototype based on a widely used data mining software WEKA, for practical data analysis. DPWeka includes a suite of differential privacy preserving computation blocks which support a variety of data analysis tasks including test statistics calculation, regression analysis, and interactive exploratory data analysis. We illustrate the use of DPWeka on genome wide association studies that include privately selecting significant SNPs and running logistic regression based on various differential privacy mechanisms.