PIR with Compressed Queries and Amortized Query Processing

Explore a groundbreaking conference talk on improving the efficiency of Private Information Retrieval (PIR) systems. Delve into two innovative techniques presented by Sebastian Angel from UT Austin and NYU at the 2018 IEEE Symposium on Security & Privacy. Learn about a query compression method that achieves significant size reductions for CPU-efficient CPIR protocols. Discover a novel data encoding called probabilistic batch codes (PBCs) that enables multi-query PIR schemes to amortize computational costs. Examine the practical applications of these techniques in the Pung private communication system, resulting in substantial improvements in network costs and throughput. Gain insights into cutting-edge research that enhances the performance and practicality of privacy-preserving systems.

PIR with Compressed Queries and Amortized Query Processing