Negotiating Privacy/Utility Trade-Offs under Differential Privacy

Thursday, June 23, 2022 - 9:15 am9:35 am

Gerome Miklau, CEO/Founder, Tumult Labs and Professor, University of Massachusetts Amherst


Differential privacy is a model of privacy protection currently being adopted by commercial enterprises and government institutions. Using differential privacy, data custodians can share data in new ways while quantifying the potential privacy loss incurred by individuals present in the data. However the choice to limit privacy loss in the model of differential privacy must be weighed against the impact on the accuracy of the data shared.

The full complexity of making choices about privacy/utility trade-offs has rarely been considered by the research community. Using a real case study of Internal Revenue Service data shared with the Department of Education, we describe the social and technical challenges faced by data custodians as they negotiate with data consumers to establish standards for data release.

Gerome Miklau, Tumult Labs and University of Massachusetts Amherst

Gerome Miklau is CEO and co-founder of Tumult Labs, whose mission is expanding the use and sharing of data while respecting individual privacy. He is also a Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst, where his research focuses on private, secure, and equitable data management. He received the ACM PODS Test-of-Time Award in 2020 and 2012, the Best Paper Award at the International Conference of Database Theory in 2013, and an NSF CAREER Award in 2007.

@conference {280308,
author = {Gerome Miklau},
title = {Negotiating {Privacy/Utility} {Trade-Offs} under Differential Privacy},
year = {2022},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = jun

Presentation Video