Please note: This PhD seminar will be given online.
Chang Ge, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ihab Ilyas
Data analytics is being widely used in businesses. In many cases, conducting enterprise data analytics faces two practical challenges: 1) the datasets usually contain sensitive and private information and do not allow unfettered access; and 2) these data are often owned by multiple parties and stored in silos with different access control. Therefore, it’s often required to do analytics on private siloed data.
In this talk, I discuss the challenges and introduce three systems that enable private data exploring, sampling, and profiling. On private data exploration, I describe our work in APEx for accuracy-aware differentially private data exploration; on private data sampling, I talk about the Kamino system for constraint-aware differentially private data synthesis; and on private data profiling, I introduce our work in SMFD for secure multi-party functional dependency discovery.