Galois to develop new privacy-preserving and data-sharing platform
The U.S. Department of Energy recently awarded Galois a grant to develop TRIFECTA, a new platform that accommodates data privacy and data analysis.
Collecting and storing massive amounts of data is the norm for many organizations. Data storage is inexpensive, and the data helps inform decision-making across multiple levels of an organization. For example, these datasets help network researchers discover data-mining insights and cybersecurity experts analyze potential security holes.
Unfortunately, network data may contain personally identifiable information or details of sensitive network structures.
Galois’s TRIFECTA aims to achieve a stronger combination of utility preservation and privacy protection. Specifically, data contributors are given strong and quantifiable guarantees regarding how much information can be learned about them based on their decision to contribute. Additionally, data analysts are able to link datasets from multiple sources and extract useful analysis results – as if they had access to each original raw dataset. These capabilities are made possible through our combined use of secure hardware enclaves, differential privacy, and formal methods.
Our use of secure hardware provides a solution to secure access. In addition, our combined use of differential privacy and formal methods provides a solution for utility preservation and privacy protection. This combination can also serve as “tuning knobs” for navigating the tension between utility and privacy concerns.
TRIFECTA builds on two prototypes built by PIs Dr. Darais (in collaboration with Phillip Nguyen, Alex Silence, and Joseph P. Near, funded by NSF and ODNI/IARPA) and Dr. Archer (funded by DHS) that exhibit many of our proposed capabilities.
The grant is part of the Department of Energy’s Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR), which aims to transfer DOE-supported science and technology breakthroughs into viable technology.