Abstract: Large amounts of data are collected about individuals by a variety of organizations, including government agencies, banks, hospitals, research institutions, and private companies. Many of these organizations collect similar data, or data about similar populations. Sharing this data between organizations could bring about many benefits in social, scientific, business, and security domains. For example, by sharing their data, hospitals and small clinics can obtain statistically significant results in cases where the individual datasets are otherwise too small. Unfortunately, much of the collected data is sensitive: it contains personal details about individuals or information that may damage an organization’s reputation and competitiveness. The sharing of data is hence often curbed for ethical, legal, or business reasons. Starting in May 2016, the National Science Foundation is funding a project focused on computing over distributed sensitive data. This project develops a collection of tools that will enable the benefits of data sharing without requiring data owners to share their data. The techniques developed respect principles of data ownership and privacy requirements, and draw on recent scientific developments in privacy, cryptography, machine learning, computational statistics, program verification, and system security. This talk will present an overview of the research directions currently pursued under this project. The PIs are Stephen Chong (Harvard), Marco Gaboardi (University at Buffalo), James Honaker (Harvard), Kobbi Nissim (Georgetown University), and Salil Vadhan (Harvard).
Bio: Stephen Chong is a Gordon McKay Professor of Computer Science in the Harvard John A. Paulson School of Engineering and Applied Sciences, and a participant of the Privacy Tools Project throughout its lifetime. Steve's research focuses on programming languages, information security, and the intersection of these two areas. He is the recipient of an NSF CAREER award, an AFOSR Young Investigator award, and a Sloan Research Fellowship. He received a PhD from Cornell University, and a bachelor's degree from Victoria University of Wellington, New Zealand.
