The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy
Cynthia Dwork, Jonathan Ullman · Journal of Privacy and Confidentiality · 2018
Differential Privacy is a popular technology for privacy-preserving analysis of large datasets. DP is powerful, but it requires that the analyst interact with data only through a special interface; in particular, the analyst does not see raw data, an uncomfortable situation for anyone trained in classical statistical data analysis. In this note we discuss the (overly) simple problem of allowing a trusted analyst to choose an ``"interesting" statistic for popular release (the actual computation of the chosen statistic will be carried out in a differentially private way).