Ling Ren
June 17, 2022 at 11:00 AM on Zoom / Soda Hall
Practical Single-server Private Information Retrieval
Abstract: In this talk, I will present our recent results on practical single-server private information retrieval (PIR). I will first present OnionPIR, a single-server PIR protocol that significantly improves the response size. OnionPIR utilizes recent advances in leveled fully homomorphic encryption (FHE) and carefully composes different lattice-based FHE schemes and homomorphic operations to control the noise growth and response size. OnionPIR achieves a response overhead of just 4x (over the insecure baseline), in contrast to the 100x response overhead of previous schemes. For a database with one million entries each of 30 KB, the request size and response size of OnionPIR are 128 KB. One limitation of existing single-server PIR schemes (OnionPIR included) is that they are efficient only for relatively large database entries (e.g., at least 30 KB). In the second part of my talk, I will outline our approach to efficiently handling small records when the client has a batch of entries to retrieve.
Bio: Ling Ren is an assistant professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Prior to joining the University of Illinois, he obtained his Ph.D. from MIT and worked at VMware Research. His research interests include security, cryptography, and distributed algorithms. He has won several awards including NSF CAREER Award, Google privacy research award, VMware Early Career Faculty Grant, Top Picks in Hardware and Embedded Security, and Best Paper Runner-Up and Best Student Paper at CCS.