vSQL: Verifying Arbitrary SQL Queries over Dynamic Outsourced Databases

Yupeng Zhang, Daniel Genkin, Jonathan Katz, D. Papadopoulos, Charalampos Papamanthou
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引用次数: 141

Abstract

Cloud database systems such as Amazon RDS or Google Cloud SQLenable the outsourcing of a large database to a server who then responds to SQL queries. A natural problem here is to efficiently verify the correctness of responses returned by the (untrusted) server. In this paper we present vSQL, a novel cryptographic protocol for publicly verifiable SQL queries on dynamic databases. At a high level, our construction relies on two extensions of the CMT interactive-proof protocol [Cormode et al., 2012]: (i) supporting outsourced input via the use of a polynomial-delegation protocol with succinct proofs, and (ii) supporting auxiliary input (i.e., non-deterministic computation) efficiently. Compared to previous verifiable-computation systems based on interactive proofs, our construction has verification cost polylogarithmic in the auxiliary input (which for SQL queries can be as large as the database) rather than linear. In order to evaluate the performance and expressiveness of our scheme, we tested it on SQL queries based on the TPC-H benchmark on a database with 6 million rows and 13 columns. The server overhead in our scheme (which is typically the main bottleneck) is up to 120 times lower than previousapproaches based on succinct arguments of knowledge (SNARKs), and moreover we avoid the need for query-dependent pre-processing which is required by optimized SNARK-based schemes. In our construction, the server/client time and the communication cost are comparable to, and sometimessmaller than, those of existing customized solutions which only support specific queries.
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vSQL:验证动态外包数据库上的任意SQL查询
云数据库系统(如Amazon RDS或Google Cloud SQLenable)可以将大型数据库外包给服务器,然后由服务器响应SQL查询。这里的一个自然问题是有效地验证(不受信任的)服务器返回的响应的正确性。本文提出了一种用于动态数据库上可公开验证的SQL查询的新型加密协议vSQL。在高层次上,我们的构建依赖于CMT交互证明协议的两个扩展[Cormode等人,2012]:(i)通过使用具有简洁证明的多项式委托协议来支持外包输入,以及(ii)有效地支持辅助输入(即非确定性计算)。与以前基于交互式证明的可验证计算系统相比,我们的结构在辅助输入(SQL查询可以与数据库一样大)中具有多对数的验证成本,而不是线性的。为了评估我们的方案的性能和表达能力,我们在一个600万行13列的数据库上基于TPC-H基准测试了它的SQL查询。我们方案中的服务器开销(通常是主要瓶颈)比以前基于简洁知识参数(SNARKs)的方法低120倍,而且我们避免了查询相关预处理的需要,而这是基于SNARKs的优化方案所需要的。在我们的构建中,服务器/客户端时间和通信成本与仅支持特定查询的现有定制解决方案相当,有时甚至更小。
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