vChain+: Optimizing Verifiable Blockchain Boolean Range Queries

Haixin Wang, Cheng Xu, Ce Zhang, Jianliang Xu, Zhe Peng, and Jian Pei

Abstract

Blockchain has recently gained massive attention thanks to the success of cryptocurrencies and decentralized applications. With immutability and tamper-resistance features, it can be seen as a promising secure database solution. To address the need of searches over blockchain databases, prior work vChain proposed a novel verifiable processing framework that ensures query integrity without maintaining a full copy of the blockchain database. It however suffers from several limitations, including linear-scan search performance in the worst case and impractical public key management. In this paper, we propose a new searchable blockchain system, vChain+, that supports efficient verifiable boolean range queries with additional features. Specifically, we propose a sliding window accumulator index to achieve efficient query processing even for the worst case. We also design an object registration index to enable practical public key management without compromising the security guarantee. To support richer queries, we employ optimal tree-based indexes to index both keywords and numerical attributes of the data objects. Several optimizations are also proposed to further improve the query performance. Security analysis and empirical study validate the robustness and performance improvement of the proposed system. Compared with vChain, vChain+ improves the query performance by up to 913X.
Type
Conference paper
Publication
In Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE ’22)
Date
May 2022
Note
Full Paper, accepted to appear
Links