ZKSQL: Verifiable and Efiicient Query Evaluation with Zero-Knowledge Proofs

Xiling Li, Chenkai Weng, Yongxin Xu, Xiao Wang, Jennie Rogers

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

Individuals and organizations are using databases to store personal information at an unprecedented rate. This creates a quandary for data providers. They are responsible for protecting the privacy of individuals described in their database. On the other hand, data providers are sometimes required to provide statistics about their data instead of sharing it wholesale with strong assurances that these answers are correct and complete such as in regulatory filings for the US SEC and other goverment organizations. We introduce a system, ZKSQL, that provides authenticated answers to ad-hoc SQL queries with zero-knowledge proofs. Its proofs show that the answers are correct and sound with respect to the database’s contents and they do not divulge any information about its input records. This system constructs proofs over the steps in a query’s evaluation and it accelerates this process with authenticated set operations. We validate the efficiency of this approach over a suite of TPC-H queries and our results show that ZKSQL achieves two orders of magnitude speedup over the baseline.

Original languageEnglish (US)
Pages (from-to)1804-1816
Number of pages13
JournalProceedings of the VLDB Endowment
Volume16
Issue number8
DOIs
StatePublished - 2023
Event49th International Conference on Very Large Data Bases, VLDB 2023 - Vancouver, Canada
Duration: Aug 28 2023Sep 1 2023

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • General Computer Science

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