Differentially Private Synthetic Data with Private Density Estimation

arXiv:2405.04554v1 Announce Type: new
Abstract: The need to analyze sensitive data, such as medical records or financial data, has created a critical research challenge in recent years. In this paper, we adopt the framework of differential privacy, and explore mechanisms for generating an entire dataset which accurately captures characteristics of the original data. We build upon the work of Boedihardjo et al, which laid the foundations for a new optimization-based algorithm for generating private synthetic data. Importantly, we adapt their …

arxiv challenge critical cs.cr cs.it cs.lg data dataset differential privacy financial financial data framework math.it math.st medical privacy private records research sensitive sensitive data stat.ml stat.th synthetic synthetic data