Encrypted Dataset Collaboration: Intelligent Privacy for Smart Cities

The past year has seen increasing scrutiny of Smart Cities efforts with regard to privacy. Privacy advocates have criticized Smart City data collection on the whole and critiqued specific city efforts that they feel have crossed a line. Cities are struggling with a number of privacy issues, including how to address third parties’ collection of Smart City data, how cities consume personally identifying information from third-parties, and how public records laws intersect with privacy concerns. The majority of data that cities collect are subject to disclosure under public record laws, with an attendant obligation to anonymize sensitive private information. However, as the amount and availability of data increases, the ability to cross-reference, correlate, and de-anonymize or re-sensitize datasets also increases. This leads to re-identification attacks that infringe the privacy of individuals in those datasets, and fosters mistrust in city governments and technology vendors. A fundamental challenge is that open data and privacy interact in complex and unpredictable ways. Some cities may choose to allow third parties to collect and manage that data in an effort to encourage innovation in the delivery of city services, while simultaneously wrestling with the legal and policy implications, such as privacy and public records law compliance. Unfortunately, this also may have undesirable privacy outcomes depending on a third-party's use of that data and the city's role in encouraging its collection. In this paper, we will discuss concrete approaches to smart cities data privacy governance including collection and management, and specifically, an innovative pilot project supported by the U.S. Department of Homeland Security, Science & Technology Directorate aimed at demonstrating how privacy technology can help harmonize data sensitivity risks with intended benefits.