Abstract:
As databases increasingly serve as backbones for sensitive applications, ensuring both data confidentiality and computational integrity becomes critical—especially when the data owner and querier do not fully trust each other. In this talk, I will introduce PoneglyphDB, a novel database system that generates non-interactive zero-knowledge proofs (ZKPs) for arbitrary SQL queries, allowing users to verify query results without seeing the underlying data. PoneglyphDB tackles key limitations of prior interactive ZKP systems by compiling SQL operators into efficient PLONKish arithmetic circuits, optimizing them with low-degree polynomial constraints, recursive proof composition, and oblivious execution. The system supports a rich set of SQL operations including joins, aggregations, group-by, and even string predicates, while achieving significant performance improvements over state-of-the-art systems like ZKSQL and Libra. I will detail the system architecture, circuit compiler, and experimental results on the TPC-H benchmark, showing how PoneglyphDB bridges theory and practice for verifiable, privacy-preserving data processing.
Bio:
Binbin Gu is a final-year Ph.D. candidate in Computer Science at the University of California, Irvine, advised by Faisal Nawab. His research lies at the intersection of trustworthy AI, database systems, and cryptographic verification.
