BSF:2012348:The Boundaries of Privacy

California Institute Of Technology, Pasadena CA

Investigators

Abstract

This project is funded as part of the United States-Israel Collaboration in Computer Science (USICCS) program. Through this program, NSF and the United States - Israel Binational Science Foundation (BSF) jointly support collaborations among US-based researchers and Israel-based researchers. The availability of fast and cheap computers coupled with massive storage devices has enabled the collection and mining of data on a scale previously unimaginable. This opens the door to potential abuse regarding individuals' information. This work explores the fundamental tradeoffs between privacy for individuals' data and the usefulness of the information one can obtain from these large datasets. Differential privacy is a well-established paradigm aimed at mitigating the drawbacks of traditional anonymization techniques, as it provides a rigorous guarantee for the added risk to an individual in participating in a database. This research addresses fundamental questions clarifying the boundaries of what is possible under differential privacy and its relaxations, by exploring the fundamental conflicts between privacy and utility and the additional tensions introduced by computational efficiency. This work expands the potential impact of differentially private algorithms on real-world applications, and also ensures broad impact via curriculum development, pedagogical development, and outreach activities.