Collaborative Research: IMR: MM-1B: Foundations for Differentially Private Internet Measurement
Internet measurement research has been providing critical insights and evidence support in guiding the design of Internet infrastructures. However, how to share and use Internet measurement data while respecting users' privacy is still challenging. To protect privacy, most works choose to anonymize sensitive fields or only publish the aggregated statistics, but such methods are vulnerable to privacy attacks. Differential privacy, which provides guaranteed privacy protection for data release, has gained prominent traction from companies and government agencies, and is a natural choice for sharing Internet measurement data. However, a critical gap remains to identify how differential privacy can be applied to networking problems. This project aims to understand privacy issues and then lay the foundations for deploying differential privacy in the processing pipeline of Internet measurement data. The project's broader significance and importance include transferring the technologies to industry, involving members from under-represented groups, and disseminating outcomes through K-12 outreach and community services.
- Tianhao Wang. PI on this project (uVa CS).
- Zhou Li. PI on this project (UCI EECS).
- Joann Qiongna Chen. Ph.D. Student Researcher (UCI EECS).
- Danyu Sun. Ph.D. Student Researcher (UCI EECS).