Answering Summation Queries for Numerical Attributes under Differential Privacy
arXiv:1908.10268v11 citations
AI Analysis
This addresses a non-trivial privacy challenge for data analysts, but appears incremental as it builds on existing differential privacy techniques.
The paper tackled the problem of answering sum queries on numerical data under differential privacy, showing that traditional methods are suboptimal and a rigorous approach is needed for low-error algorithms.
In this work we explore the problem of answering a set of sum queries under Differential Privacy. This is a little understood, non-trivial problem especially in the case of numerical domains. We show that traditional techniques from the literature are not always the best choice and a more rigorous approach is necessary to develop low error algorithms.