Big data has created complex new challenges to data privacy. One advantage of administrative big data is the enhanced feasibility of large scale record linkage. How can we make more data available to inform decision making without creating “Big Brother”? How can we inform this needed revolution in privacy protection without cutting back access to data?
In this webinar, Cavan Capps and Micah Altman will review their comprehensive analysis of an ACS use case that can be used to inform key decisions on how to protect data privacy while leveraging the latest data technologies. The results suggest that a multi-tiered access system to the data may be warranted in the future, potentially including traditional tabulations and regressions protected by Differential Privacy or variants of Secure Multi-party Computing (SMC) in software or in hardware using SGX, among other options. The webinar will discuss some of the strengths and weaknesses of the tools mentioned above and propose how such an infrastructure might be constructed.
Finally, the webinar will provide an update on our work continuing work to examine the practical use of SGX-SMC and software based SMC for data collection and integrating shared confidential data from different sources. This enables data sharing while maintaining individual privacy of individual during any analysis. Differential privacy will be used to ensure that any outputs remain confidential.
Micah Altman, Head Research Scientist, MIT Libraries
Cavan Capps, Big Data Lead, U.S. Census Bureau